--- EXPERIMENT NOTES
Not all of the following information may be relevant for the case being handled, since this project may be part of a much larger auto-PSS-genome project where several methods of detection of positively selected sites have been used. As such the aligned.score_ascii file may have more sequences than the file effectively used to detect positively selected codons, since the content of this file reflects the content of the file used for the master alignment, from which a subsample may have been taken.
#
### General parameters ###
#
# The maximum number of sequences to use for the master file
sequence_limit=90
# The random seed
random_seed=3976763
#
### Alignment ###
#
# The alignment method: clustalw, muscle, kalign, t_coffee, or amap
align_method=muscle
# Minimum support value for amino acid positions in the alignment
tcoffee_min_score=3
#
### MrBayes ###
#
# Number of iterations in MrBayes
mrbayes_generations=1000000
# MrBayes burnin
mrbayes_burnin=2500
#
### FUBAR ###
#
# The maximum number of sequences to be used by FUBAR.
fubar_sequence_limit=90
# The number of FUBAR runs
fubar_runs=1
#
### codeML ###
#
# The maximum number of sequences to be used by CodeML
codeml_sequence_limit=30
# The number of CodeML runs
codeml_runs=1
# The CodeML models to be run, one or more of: '1', '2', '7', and/or '8'.
codeml_models=1 2 7 8
#
### OmegaMap ###
#
# The maximum number of sequences to use in OmegaMap
omegamap_sequence_limit=90
# The number of OmegaMap runs
omegamap_runs=1
# The number of OmegaMap iterations
omegamap_iterations=2500
--- EXPERIMENT PROPERTIES
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/data/mrbayes_input.nex.run1.p" and "/data/mrbayes_input.nex.run2.p":
(Use the harmonic mean for Bayes factor comparisons of models)
(Values are saved to the file /data/mrbayes_input.nex.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1688.12 -1715.08
2 -1689.58 -1718.83
--------------------------------------
TOTAL -1688.60 -1718.16
--------------------------------------
Model parameter summaries over the runs sampled in files
"/data/mrbayes_input.nex.run1.p" and "/data/mrbayes_input.nex.run2.p":
Summaries are based on a total of 3002 samples from 2 runs.
Each run produced 2001 samples of which 1501 samples were included.
Parameter summaries saved to file "/data/mrbayes_input.nex.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.120030 0.000253 0.088427 0.149303 0.119003 1024.47 1189.67 1.000
r(A<->C){all} 0.018073 0.000301 0.000003 0.052427 0.013106 487.71 534.06 1.000
r(A<->G){all} 0.204244 0.002232 0.117116 0.297482 0.200120 534.16 578.09 1.000
r(A<->T){all} 0.038181 0.000219 0.012680 0.067539 0.036179 827.33 902.96 1.003
r(C<->G){all} 0.023248 0.000544 0.000005 0.069301 0.016036 582.42 638.27 1.003
r(C<->T){all} 0.628434 0.003234 0.517576 0.734594 0.630819 589.07 625.89 1.001
r(G<->T){all} 0.087819 0.000650 0.038621 0.135669 0.085568 772.95 830.22 1.000
pi(A){all} 0.251390 0.000203 0.222291 0.277740 0.251077 1152.82 1166.98 1.000
pi(C){all} 0.124868 0.000115 0.104527 0.145533 0.124464 1033.74 1089.21 1.000
pi(G){all} 0.197673 0.000169 0.174426 0.224119 0.197007 1118.39 1205.53 1.000
pi(T){all} 0.426070 0.000256 0.396225 0.458055 0.426005 1025.29 1138.20 1.001
alpha{1,2} 0.178722 0.062543 0.000047 0.530809 0.110128 1077.44 1123.65 1.000
alpha{3} 2.055394 1.394859 0.315402 4.359189 1.829020 1174.67 1177.48 1.000
pinvar{all} 0.230526 0.018712 0.000432 0.470827 0.220687 1031.33 1112.79 1.000
------------------------------------------------------------------------------------------------------
* Convergence diagnostic (ESS = Estimated Sample Size); min and avg values
correspond to minimal and average ESS among runs.
ESS value below 100 may indicate that the parameter is undersampled.
+ Convergence diagnostic (PSRF = Potential Scale Reduction Factor; Gelman
and Rubin, 1992) should approach 1.0 as runs converge.
--- CODEML SUMMARY
Model 1: NearlyNeutral -1616.101155
Model 2: PositiveSelection -1616.101155
Model 7: beta -1615.595872
Model 8: beta&w>1 -1615.595872
Model 2 vs 1 0
Model 8 vs 7 0
-- Starting log on Fri Nov 18 14:40:18 GMT 2022 --
-- Iteration: /working_dir/input/2_modified/DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result--
-- Starting log on Fri Nov 18 14:58:29 GMT 2022 --
-- Iteration: /working_dir/input/2_modified/DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result--
-- Starting log on Sat Nov 19 03:31:29 GMT 2022 --
-- Iteration: /working_dir/pss_subsets/DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result/gapped_alignment/codeml,DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result.1--
MrBayes v3.2.6 x64
(Bayesian Analysis of Phylogeny)
Distributed under the GNU General Public License
Type "help" or "help <command>" for information
on the commands that are available.
Type "about" for authorship and general
information about the program.
Executing file "/data/mrbayes_input.nex"
UNIX line termination
Longest line length = 63
Parsing file
Expecting NEXUS formatted file
Reading data block
Allocated taxon set
Allocated matrix
Defining new matrix with 30 taxa and 861 characters
Missing data coded as ?
Data matrix is interleaved
Data is Dna
Gaps coded as -
Matching characters coded as .
Taxon 1 -> C216
Taxon 2 -> C7
Taxon 3 -> C53
Taxon 4 -> C113
Taxon 5 -> C173
Taxon 6 -> C197
Taxon 7 -> C242
Taxon 8 -> C11
Taxon 9 -> C36
Taxon 10 -> C57
Taxon 11 -> C82
Taxon 12 -> C85
Taxon 13 -> C78
Taxon 14 -> C238
Taxon 15 -> C281
Taxon 16 -> C60
Taxon 17 -> C178
Taxon 18 -> C32
Taxon 19 -> C71
Taxon 20 -> C66
Taxon 21 -> C124
Taxon 22 -> C65
Taxon 23 -> C130
Taxon 24 -> C131
Taxon 25 -> C72
Taxon 26 -> C77
Taxon 27 -> C136
Taxon 28 -> C93
Taxon 29 -> C79
Taxon 30 -> C84
Successfully read matrix
Setting default partition (does not divide up characters)
Setting model defaults
Seed (for generating default start values) = 1668828692
Setting output file names to "/data/mrbayes_input.nex.run<i>.<p|t>"
Exiting data block
Reading mrbayes block
Setting autoclose to yes
Setting nowarnings to yes
Defining charset called 'first_pos'
Defining charset called 'second_pos'
Defining charset called 'third_pos'
Defining partition called 'by_codon'
Setting by_codon as the partition, dividing characters into 3 parts.
Setting model defaults
Seed (for generating default start values) = 985504745
Setting Nst to 6 for partition 1
Setting Nst to 6 for partition 2
Setting Nst to 6 for partition 3
Setting Rates to Invgamma for partition 1
Setting Rates to Invgamma for partition 2
Setting Rates to Invgamma for partition 3
Successfully set likelihood model parameters to all
applicable data partitions
Unlinking
Setting number of generations to 1000000
Running Markov chain
MCMC stamp = 8957953449
Seed = 963043440
Swapseed = 1668828692
Model settings:
Settings for partition 1 --
Datatype = DNA
Nucmodel = 4by4
Nst = 6
Substitution rates, expressed as proportions
of the rate sum, have a Dirichlet prior
(1.00,1.00,1.00,1.00,1.00,1.00)
Covarion = No
# States = 4
State frequencies have a Dirichlet prior
(1.00,1.00,1.00,1.00)
Rates = Invgamma
The distribution is approximated using 4 categories.
Likelihood summarized over all rate categories in each generation.
Shape parameter is exponentially
distributed with parameter (1.00).
Proportion of invariable sites is uniformly dist-
ributed on the interval (0.00,1.00).
Settings for partition 2 --
Datatype = DNA
Nucmodel = 4by4
Nst = 6
Substitution rates, expressed as proportions
of the rate sum, have a Dirichlet prior
(1.00,1.00,1.00,1.00,1.00,1.00)
Covarion = No
# States = 4
State frequencies have a Dirichlet prior
(1.00,1.00,1.00,1.00)
Rates = Invgamma
The distribution is approximated using 4 categories.
Likelihood summarized over all rate categories in each generation.
Shape parameter is exponentially
distributed with parameter (1.00).
Proportion of invariable sites is uniformly dist-
ributed on the interval (0.00,1.00).
Settings for partition 3 --
Datatype = DNA
Nucmodel = 4by4
Nst = 6
Substitution rates, expressed as proportions
of the rate sum, have a Dirichlet prior
(1.00,1.00,1.00,1.00,1.00,1.00)
Covarion = No
# States = 4
State frequencies have a Dirichlet prior
(1.00,1.00,1.00,1.00)
Rates = Invgamma
The distribution is approximated using 4 categories.
Likelihood summarized over all rate categories in each generation.
Shape parameter is exponentially
distributed with parameter (1.00).
Proportion of invariable sites is uniformly dist-
ributed on the interval (0.00,1.00).
Active parameters:
Partition(s)
Parameters 1 2 3
---------------------------
Revmat 1 1 1
Statefreq 2 2 2
Shape 3 3 4
Pinvar 5 5 5
Ratemultiplier 6 6 6
Topology 7 7 7
Brlens 8 8 8
---------------------------
Parameters can be linked or unlinked across partitions using 'link' and 'unlink'
1 -- Parameter = Revmat{all}
Type = Rates of reversible rate matrix
Prior = Dirichlet(1.00,1.00,1.00,1.00,1.00,1.00)
Partitions = All
2 -- Parameter = Pi{all}
Type = Stationary state frequencies
Prior = Dirichlet
Partitions = All
3 -- Parameter = Alpha{1,2}
Type = Shape of scaled gamma distribution of site rates
Prior = Exponential(1.00)
Partitions = 1 and 2
4 -- Parameter = Alpha{3}
Type = Shape of scaled gamma distribution of site rates
Prior = Exponential(1.00)
Partition = 3
5 -- Parameter = Pinvar{all}
Type = Proportion of invariable sites
Prior = Uniform(0.00,1.00)
Partitions = All
6 -- Parameter = Ratemultiplier{all}
Type = Partition-specific rate multiplier
Prior = Fixed(1.0)
Partitions = All
7 -- Parameter = Tau{all}
Type = Topology
Prior = All topologies equally probable a priori
Partitions = All
Subparam. = V{all}
8 -- Parameter = V{all}
Type = Branch lengths
Prior = Unconstrained:GammaDir(1.0,0.1000,1.0,1.0)
Partitions = All
The MCMC sampler will use the following moves:
With prob. Chain will use move
0.91 % Dirichlet(Revmat{all})
0.91 % Slider(Revmat{all})
0.91 % Dirichlet(Pi{all})
0.91 % Slider(Pi{all})
1.82 % Multiplier(Alpha{1,2})
1.82 % Multiplier(Alpha{3})
1.82 % Slider(Pinvar{all})
9.09 % ExtSPR(Tau{all},V{all})
9.09 % ExtTBR(Tau{all},V{all})
9.09 % NNI(Tau{all},V{all})
9.09 % ParsSPR(Tau{all},V{all})
36.36 % Multiplier(V{all})
12.73 % Nodeslider(V{all})
5.45 % TLMultiplier(V{all})
Division 1 has 14 unique site patterns
Division 2 has 15 unique site patterns
Division 3 has 44 unique site patterns
Initializing conditional likelihoods
Using standard SSE likelihood calculator for division 1 (single-precision)
Using standard SSE likelihood calculator for division 2 (single-precision)
Using standard SSE likelihood calculator for division 3 (single-precision)
Initializing invariable-site conditional likelihoods
Initial log likelihoods and log prior probs for run 1:
Chain 1 -- -3672.517094 -- 82.122948
Chain 2 -- -3626.441489 -- 82.122948
Chain 3 -- -3578.868158 -- 82.122948
Chain 4 -- -3363.844604 -- 82.122948
Initial log likelihoods and log prior probs for run 2:
Chain 1 -- -3546.023374 -- 82.122948
Chain 2 -- -3392.876341 -- 82.122948
Chain 3 -- -3521.276428 -- 82.122948
Chain 4 -- -3361.554561 -- 82.122948
Using a relative burnin of 25.0 % for diagnostics
Chain results (1000000 generations requested):
0 -- [-3672.517] (-3626.441) (-3578.868) (-3363.845) * [-3546.023] (-3392.876) (-3521.276) (-3361.555)
1000 -- (-1864.615) (-1994.462) [-1804.340] (-1879.565) * (-1869.897) (-1861.299) [-1844.130] (-1875.067) -- 0:00:00
2000 -- (-1755.727) (-1879.370) [-1749.154] (-1783.576) * (-1735.567) (-1762.713) (-1742.910) [-1747.686] -- 0:08:19
3000 -- (-1738.007) (-1752.811) [-1713.161] (-1750.178) * [-1704.695] (-1757.467) (-1715.169) (-1734.818) -- 0:11:04
4000 -- (-1712.939) (-1741.801) [-1718.437] (-1729.236) * [-1703.349] (-1737.242) (-1712.736) (-1710.302) -- 0:08:18
5000 -- [-1718.375] (-1719.376) (-1717.055) (-1719.324) * (-1701.682) (-1720.467) (-1706.351) [-1703.979] -- 0:09:57
Average standard deviation of split frequencies: 0.083512
6000 -- [-1712.575] (-1713.092) (-1706.986) (-1721.491) * (-1718.119) (-1713.068) [-1707.594] (-1710.589) -- 0:11:02
7000 -- (-1732.068) (-1714.496) [-1709.226] (-1719.718) * (-1706.718) [-1706.227] (-1710.538) (-1704.916) -- 0:09:27
8000 -- [-1709.256] (-1712.203) (-1723.001) (-1724.392) * (-1717.467) [-1699.537] (-1710.581) (-1725.578) -- 0:10:20
9000 -- (-1706.073) (-1732.333) [-1713.987] (-1724.150) * (-1701.902) (-1721.421) [-1694.820] (-1702.755) -- 0:11:00
10000 -- (-1701.490) (-1711.681) [-1705.710] (-1714.677) * (-1707.619) (-1711.396) (-1717.005) [-1709.611] -- 0:09:54
Average standard deviation of split frequencies: 0.070245
11000 -- (-1705.109) (-1706.986) [-1704.165] (-1715.115) * [-1703.048] (-1718.893) (-1712.830) (-1709.974) -- 0:10:29
12000 -- (-1704.934) (-1705.679) [-1705.032] (-1716.548) * [-1699.673] (-1719.951) (-1699.241) (-1720.126) -- 0:10:58
13000 -- (-1713.082) (-1713.124) [-1702.943] (-1743.750) * (-1709.050) (-1714.311) [-1702.812] (-1707.368) -- 0:10:07
14000 -- (-1712.271) (-1723.414) [-1700.102] (-1730.755) * (-1732.221) [-1712.017] (-1726.268) (-1706.973) -- 0:10:33
15000 -- (-1705.733) (-1721.698) [-1696.958] (-1708.968) * (-1723.960) (-1704.143) [-1699.279] (-1694.096) -- 0:10:56
Average standard deviation of split frequencies: 0.062369
16000 -- (-1707.947) [-1694.722] (-1704.041) (-1725.865) * (-1719.231) (-1715.588) (-1715.147) [-1695.656] -- 0:10:15
17000 -- (-1717.852) (-1708.849) [-1700.073] (-1711.376) * (-1706.935) (-1712.341) [-1701.629] (-1712.645) -- 0:10:36
18000 -- (-1702.847) (-1711.332) [-1700.722] (-1722.049) * (-1712.371) (-1711.678) (-1706.029) [-1702.301] -- 0:10:54
19000 -- (-1696.891) (-1700.951) (-1707.683) [-1705.238] * (-1714.840) (-1706.961) [-1692.550] (-1718.336) -- 0:10:19
20000 -- (-1707.606) (-1705.743) [-1694.024] (-1702.930) * (-1699.711) [-1712.627] (-1712.093) (-1713.425) -- 0:10:37
Average standard deviation of split frequencies: 0.062410
21000 -- (-1704.471) [-1705.699] (-1718.514) (-1708.211) * (-1706.875) [-1689.797] (-1706.543) (-1704.841) -- 0:10:52
22000 -- [-1696.528] (-1711.571) (-1716.986) (-1701.401) * (-1707.879) (-1697.843) (-1713.452) [-1703.722] -- 0:10:22
23000 -- (-1711.929) [-1716.482] (-1719.093) (-1729.562) * (-1715.595) (-1700.121) [-1703.904] (-1716.778) -- 0:10:37
24000 -- (-1717.468) [-1699.341] (-1703.510) (-1694.454) * (-1706.744) [-1691.326] (-1711.775) (-1708.633) -- 0:10:50
25000 -- [-1704.001] (-1708.373) (-1715.046) (-1694.859) * (-1711.299) [-1696.971] (-1696.724) (-1723.840) -- 0:10:24
Average standard deviation of split frequencies: 0.054846
26000 -- (-1712.451) [-1700.776] (-1711.779) (-1699.498) * (-1717.473) [-1698.331] (-1710.701) (-1707.586) -- 0:10:36
27000 -- (-1731.148) [-1696.085] (-1699.037) (-1713.400) * [-1701.231] (-1712.837) (-1718.028) (-1726.674) -- 0:10:48
28000 -- (-1713.873) (-1713.376) [-1696.972] (-1706.793) * [-1699.015] (-1711.184) (-1714.288) (-1727.587) -- 0:10:24
29000 -- (-1714.687) [-1706.895] (-1700.839) (-1698.655) * [-1702.671] (-1699.129) (-1709.325) (-1714.714) -- 0:10:36
30000 -- (-1702.115) [-1694.791] (-1709.527) (-1699.975) * (-1718.616) [-1698.367] (-1710.571) (-1709.430) -- 0:10:46
Average standard deviation of split frequencies: 0.043486
31000 -- [-1708.045] (-1704.052) (-1713.584) (-1705.211) * [-1704.006] (-1700.612) (-1693.733) (-1714.625) -- 0:10:25
32000 -- [-1697.611] (-1710.453) (-1701.376) (-1717.440) * (-1713.189) (-1714.784) (-1704.927) [-1703.203] -- 0:10:35
33000 -- (-1694.832) (-1703.620) (-1702.633) [-1706.969] * (-1715.956) (-1691.934) (-1706.684) [-1693.971] -- 0:10:44
34000 -- [-1690.372] (-1729.084) (-1706.722) (-1699.729) * (-1734.881) (-1683.964) (-1711.478) [-1698.977] -- 0:10:25
35000 -- (-1693.252) (-1723.393) [-1695.444] (-1710.861) * (-1723.539) (-1703.199) [-1693.540] (-1708.697) -- 0:10:34
Average standard deviation of split frequencies: 0.037413
36000 -- (-1716.952) (-1704.109) [-1696.628] (-1715.910) * (-1718.584) [-1695.586] (-1710.332) (-1695.503) -- 0:10:42
37000 -- (-1717.734) (-1704.522) [-1697.366] (-1702.792) * (-1712.482) (-1704.355) [-1714.656] (-1714.460) -- 0:10:24
38000 -- (-1714.749) (-1690.105) (-1707.361) [-1696.659] * (-1707.954) (-1715.935) [-1694.098] (-1705.047) -- 0:10:32
39000 -- (-1703.882) (-1714.769) [-1706.894] (-1700.834) * (-1706.222) (-1702.552) (-1709.961) [-1698.654] -- 0:10:40
40000 -- [-1688.751] (-1723.281) (-1715.039) (-1710.018) * [-1711.533] (-1712.052) (-1723.291) (-1705.692) -- 0:10:48
Average standard deviation of split frequencies: 0.034951
41000 -- [-1702.906] (-1708.520) (-1723.806) (-1722.127) * [-1697.460] (-1695.523) (-1716.575) (-1698.327) -- 0:10:31
42000 -- (-1697.266) [-1709.667] (-1717.208) (-1703.935) * (-1716.302) [-1701.269] (-1707.060) (-1712.841) -- 0:10:38
43000 -- [-1703.540] (-1698.177) (-1704.382) (-1709.837) * [-1703.051] (-1733.142) (-1711.514) (-1698.818) -- 0:10:45
44000 -- (-1714.520) (-1697.796) [-1694.106] (-1720.498) * (-1714.909) (-1720.263) [-1698.662] (-1711.355) -- 0:10:30
45000 -- (-1712.426) [-1702.198] (-1702.841) (-1708.471) * [-1702.810] (-1710.715) (-1703.518) (-1718.754) -- 0:10:36
Average standard deviation of split frequencies: 0.028694
46000 -- (-1719.938) (-1709.885) [-1700.527] (-1694.384) * (-1709.230) [-1715.397] (-1706.673) (-1713.921) -- 0:10:42
47000 -- (-1723.613) [-1711.437] (-1703.498) (-1709.797) * (-1718.782) [-1703.937] (-1710.734) (-1702.215) -- 0:10:28
48000 -- (-1727.768) (-1719.777) [-1704.851] (-1710.530) * [-1700.509] (-1712.785) (-1700.045) (-1712.304) -- 0:10:34
49000 -- [-1707.612] (-1712.365) (-1698.883) (-1699.360) * (-1698.649) (-1701.148) [-1703.206] (-1710.132) -- 0:10:40
50000 -- (-1716.783) (-1696.885) (-1718.936) [-1693.571] * [-1697.474] (-1708.426) (-1723.417) (-1701.877) -- 0:10:27
Average standard deviation of split frequencies: 0.031059
51000 -- [-1707.729] (-1706.867) (-1713.058) (-1698.906) * [-1706.680] (-1724.176) (-1692.743) (-1702.155) -- 0:10:32
52000 -- (-1712.659) (-1709.403) (-1702.649) [-1704.958] * (-1692.688) (-1703.508) [-1694.151] (-1725.506) -- 0:10:38
53000 -- (-1709.821) [-1706.656] (-1695.509) (-1726.042) * (-1705.129) [-1702.600] (-1709.703) (-1707.636) -- 0:10:25
54000 -- (-1703.773) (-1713.735) [-1695.492] (-1723.435) * (-1705.655) (-1700.676) [-1697.491] (-1703.613) -- 0:10:30
55000 -- [-1706.907] (-1710.450) (-1695.926) (-1718.908) * (-1708.528) (-1696.750) [-1700.693] (-1701.233) -- 0:10:35
Average standard deviation of split frequencies: 0.028315
56000 -- (-1715.817) (-1698.850) [-1698.463] (-1725.229) * (-1705.077) (-1702.880) (-1710.990) [-1689.676] -- 0:10:23
57000 -- (-1720.485) (-1702.238) (-1706.478) [-1702.962] * (-1714.218) (-1699.001) (-1708.135) [-1691.316] -- 0:10:28
58000 -- (-1717.115) (-1692.153) (-1711.581) [-1685.549] * (-1699.160) [-1692.153] (-1713.132) (-1692.040) -- 0:10:33
59000 -- (-1714.469) (-1700.163) [-1697.717] (-1703.475) * (-1710.917) [-1704.828] (-1709.226) (-1705.449) -- 0:10:22
60000 -- (-1700.311) (-1706.864) (-1702.488) [-1728.815] * (-1708.573) (-1705.717) [-1698.497] (-1698.809) -- 0:10:26
Average standard deviation of split frequencies: 0.026832
61000 -- (-1716.140) (-1700.882) [-1696.997] (-1730.822) * (-1712.343) (-1710.369) (-1709.853) [-1689.398] -- 0:10:31
62000 -- (-1709.165) (-1694.926) [-1693.377] (-1726.468) * (-1710.470) [-1702.911] (-1700.908) (-1698.947) -- 0:10:20
63000 -- (-1718.873) (-1707.580) [-1691.332] (-1698.530) * (-1707.903) [-1700.348] (-1721.235) (-1697.246) -- 0:10:24
64000 -- (-1710.249) (-1710.123) [-1706.377] (-1702.683) * (-1698.153) [-1709.554] (-1714.509) (-1717.939) -- 0:10:28
65000 -- (-1701.506) [-1720.535] (-1726.518) (-1712.095) * (-1709.277) (-1706.713) (-1722.228) [-1712.864] -- 0:10:18
Average standard deviation of split frequencies: 0.027017
66000 -- (-1707.994) (-1704.863) (-1714.170) [-1696.066] * (-1722.163) [-1697.670] (-1712.869) (-1708.264) -- 0:10:22
67000 -- (-1697.964) [-1699.089] (-1711.822) (-1728.369) * (-1708.928) (-1712.027) [-1709.173] (-1715.050) -- 0:10:26
68000 -- (-1713.216) [-1692.944] (-1723.332) (-1704.173) * (-1717.708) (-1703.836) [-1696.303] (-1711.281) -- 0:10:16
69000 -- (-1716.987) [-1706.720] (-1726.215) (-1699.510) * (-1699.524) (-1719.240) [-1715.176] (-1705.683) -- 0:10:20
70000 -- (-1713.897) (-1712.873) (-1719.021) [-1693.498] * (-1711.326) (-1715.041) (-1710.393) [-1697.919] -- 0:10:24
Average standard deviation of split frequencies: 0.023642
71000 -- (-1720.899) [-1700.840] (-1714.369) (-1708.443) * (-1720.704) (-1698.473) [-1717.940] (-1709.434) -- 0:10:14
72000 -- (-1720.266) (-1710.497) (-1703.962) [-1708.133] * [-1706.575] (-1698.198) (-1721.587) (-1717.815) -- 0:10:18
73000 -- (-1728.532) [-1704.374] (-1696.380) (-1732.101) * [-1694.909] (-1702.078) (-1708.735) (-1719.745) -- 0:10:22
74000 -- (-1714.809) (-1703.945) [-1701.663] (-1721.223) * (-1706.996) (-1723.804) [-1695.569] (-1708.548) -- 0:10:13
75000 -- (-1723.272) (-1700.090) [-1696.034] (-1690.227) * (-1720.475) (-1698.629) [-1694.595] (-1711.416) -- 0:10:16
Average standard deviation of split frequencies: 0.024190
76000 -- [-1712.329] (-1712.570) (-1706.109) (-1701.358) * (-1710.835) (-1701.856) [-1696.014] (-1709.071) -- 0:10:20
77000 -- (-1708.558) (-1707.094) (-1701.903) [-1692.801] * (-1710.254) [-1703.709] (-1707.844) (-1719.322) -- 0:10:11
78000 -- (-1736.932) [-1694.859] (-1719.702) (-1701.982) * (-1716.991) (-1702.386) [-1697.227] (-1712.620) -- 0:10:14
79000 -- (-1712.755) (-1702.491) (-1714.925) [-1701.250] * [-1702.981] (-1709.265) (-1704.214) (-1718.590) -- 0:10:17
80000 -- (-1707.743) (-1712.646) (-1716.389) [-1697.863] * (-1697.171) (-1699.295) (-1708.002) [-1698.907] -- 0:10:09
Average standard deviation of split frequencies: 0.026917
81000 -- (-1725.006) (-1701.459) (-1703.856) [-1697.955] * (-1705.036) [-1698.304] (-1735.165) (-1712.015) -- 0:10:12
82000 -- [-1704.344] (-1718.104) (-1698.564) (-1717.338) * [-1698.501] (-1698.950) (-1716.603) (-1722.033) -- 0:10:15
83000 -- [-1696.317] (-1703.994) (-1702.113) (-1716.368) * (-1712.679) [-1697.373] (-1722.563) (-1726.341) -- 0:10:07
84000 -- (-1713.383) (-1697.517) [-1699.715] (-1705.317) * (-1708.869) [-1696.240] (-1695.122) (-1712.912) -- 0:10:10
85000 -- [-1719.893] (-1716.512) (-1703.892) (-1708.645) * (-1708.402) (-1710.477) [-1701.901] (-1702.261) -- 0:10:13
Average standard deviation of split frequencies: 0.026037
86000 -- (-1725.581) (-1713.643) (-1698.819) [-1705.111] * (-1708.735) (-1702.790) [-1692.767] (-1718.897) -- 0:10:05
87000 -- [-1708.587] (-1702.516) (-1719.215) (-1696.964) * (-1706.649) [-1702.226] (-1700.832) (-1716.333) -- 0:10:08
88000 -- (-1708.883) (-1711.937) (-1718.192) [-1704.167] * [-1704.500] (-1705.008) (-1714.533) (-1701.810) -- 0:10:11
89000 -- (-1706.809) (-1714.672) [-1709.912] (-1705.351) * (-1723.635) (-1724.051) [-1693.165] (-1702.012) -- 0:10:03
90000 -- [-1704.729] (-1697.579) (-1703.209) (-1710.163) * (-1717.680) (-1702.264) (-1712.189) [-1704.289] -- 0:10:06
Average standard deviation of split frequencies: 0.024057
91000 -- (-1695.120) (-1705.843) [-1701.509] (-1720.709) * (-1698.795) (-1703.281) (-1733.918) [-1701.942] -- 0:10:09
92000 -- [-1708.841] (-1697.427) (-1711.516) (-1717.907) * (-1712.488) (-1707.147) (-1710.592) [-1693.836] -- 0:10:02
93000 -- (-1704.752) [-1702.949] (-1714.365) (-1712.993) * [-1699.120] (-1702.634) (-1705.966) (-1713.398) -- 0:10:04
94000 -- (-1710.343) [-1700.379] (-1700.592) (-1705.907) * (-1703.108) (-1707.910) (-1704.913) [-1709.906] -- 0:10:07
95000 -- (-1701.318) [-1695.461] (-1702.369) (-1709.966) * [-1696.528] (-1703.208) (-1718.093) (-1714.488) -- 0:10:09
Average standard deviation of split frequencies: 0.024772
96000 -- (-1712.841) (-1705.253) [-1701.424] (-1714.123) * (-1715.717) (-1707.774) (-1713.755) [-1698.017] -- 0:10:02
97000 -- [-1702.808] (-1711.597) (-1704.095) (-1706.821) * [-1696.654] (-1707.263) (-1713.468) (-1712.346) -- 0:10:05
98000 -- (-1709.702) [-1699.815] (-1705.050) (-1725.779) * (-1697.061) [-1701.048] (-1707.707) (-1729.536) -- 0:10:07
99000 -- (-1702.501) (-1704.044) (-1697.102) [-1717.017] * [-1692.377] (-1696.279) (-1719.670) (-1715.299) -- 0:10:00
100000 -- (-1700.898) (-1699.862) [-1699.469] (-1719.918) * (-1715.384) (-1699.248) (-1706.570) [-1706.851] -- 0:10:03
Average standard deviation of split frequencies: 0.025722
101000 -- (-1698.536) (-1696.569) [-1712.211] (-1708.672) * [-1704.439] (-1706.910) (-1719.672) (-1697.366) -- 0:10:05
102000 -- (-1709.377) [-1691.913] (-1710.346) (-1695.936) * (-1698.679) (-1712.746) [-1700.197] (-1711.992) -- 0:09:58
103000 -- (-1709.290) (-1699.246) (-1713.498) [-1715.686] * (-1703.532) (-1722.887) [-1696.148] (-1699.704) -- 0:10:00
104000 -- (-1719.321) (-1713.343) [-1702.989] (-1718.660) * (-1704.657) (-1719.242) [-1689.831] (-1693.448) -- 0:10:03
105000 -- (-1698.131) (-1703.394) [-1695.002] (-1719.748) * (-1703.657) (-1702.280) [-1698.085] (-1703.866) -- 0:09:56
Average standard deviation of split frequencies: 0.025099
106000 -- (-1718.911) (-1700.389) [-1703.951] (-1700.160) * [-1707.406] (-1716.499) (-1691.978) (-1706.536) -- 0:09:58
107000 -- (-1710.342) (-1708.090) [-1692.129] (-1735.501) * (-1717.485) (-1720.809) [-1697.387] (-1702.457) -- 0:10:00
108000 -- (-1700.105) (-1704.590) [-1692.231] (-1708.353) * (-1723.679) (-1707.143) [-1704.058] (-1700.579) -- 0:09:54
109000 -- (-1716.858) [-1711.996] (-1691.681) (-1708.485) * (-1707.268) (-1711.758) (-1724.171) [-1694.348] -- 0:09:56
110000 -- (-1701.735) [-1693.087] (-1708.688) (-1715.061) * (-1711.054) (-1712.893) [-1702.285] (-1699.693) -- 0:09:58
Average standard deviation of split frequencies: 0.024718
111000 -- (-1706.587) [-1692.046] (-1725.311) (-1713.881) * (-1717.835) [-1697.870] (-1699.034) (-1718.148) -- 0:09:52
112000 -- [-1698.354] (-1690.394) (-1715.247) (-1710.923) * [-1702.358] (-1709.843) (-1704.246) (-1714.625) -- 0:09:54
113000 -- (-1688.159) (-1713.049) (-1709.409) [-1706.765] * [-1695.342] (-1724.791) (-1703.344) (-1705.873) -- 0:09:56
114000 -- (-1704.551) (-1711.157) (-1705.542) [-1698.961] * [-1703.994] (-1705.413) (-1715.274) (-1708.560) -- 0:09:50
115000 -- [-1695.454] (-1718.036) (-1706.329) (-1697.080) * (-1703.602) [-1692.580] (-1716.969) (-1698.808) -- 0:09:52
Average standard deviation of split frequencies: 0.024265
116000 -- [-1693.546] (-1700.972) (-1702.585) (-1720.709) * (-1714.001) [-1698.358] (-1715.270) (-1707.481) -- 0:09:54
117000 -- (-1702.159) [-1689.974] (-1717.099) (-1713.008) * (-1709.084) (-1709.269) (-1708.576) [-1700.718] -- 0:09:56
118000 -- [-1695.914] (-1688.472) (-1701.420) (-1713.407) * (-1710.194) (-1708.689) (-1711.136) [-1706.382] -- 0:09:50
119000 -- (-1708.837) [-1695.164] (-1709.928) (-1707.104) * (-1733.426) (-1696.120) (-1701.724) [-1704.583] -- 0:09:52
120000 -- (-1708.402) (-1690.911) [-1701.654] (-1701.286) * [-1709.239] (-1705.444) (-1714.459) (-1726.406) -- 0:09:54
Average standard deviation of split frequencies: 0.023049
121000 -- (-1716.372) (-1707.858) (-1717.296) [-1688.424] * [-1699.775] (-1718.895) (-1709.861) (-1722.532) -- 0:09:48
122000 -- (-1706.194) (-1717.105) (-1701.114) [-1702.178] * (-1715.950) [-1702.728] (-1713.802) (-1706.066) -- 0:09:50
123000 -- [-1693.898] (-1713.647) (-1707.002) (-1700.328) * (-1704.572) (-1708.692) [-1693.999] (-1708.514) -- 0:09:51
124000 -- [-1692.400] (-1726.289) (-1708.615) (-1710.277) * (-1710.142) (-1719.893) (-1707.879) [-1703.752] -- 0:09:46
125000 -- (-1694.068) (-1728.640) (-1704.557) [-1697.331] * (-1712.752) (-1703.373) [-1694.025] (-1726.237) -- 0:09:48
Average standard deviation of split frequencies: 0.021201
126000 -- (-1700.470) (-1718.893) (-1719.823) [-1704.375] * (-1716.823) (-1711.291) [-1697.970] (-1706.482) -- 0:09:49
127000 -- [-1700.700] (-1699.929) (-1728.823) (-1706.305) * (-1709.267) [-1696.427] (-1704.689) (-1697.765) -- 0:09:44
128000 -- [-1694.388] (-1693.495) (-1707.226) (-1702.051) * [-1694.102] (-1699.998) (-1715.241) (-1704.605) -- 0:09:45
129000 -- (-1722.753) (-1705.656) (-1706.150) [-1712.408] * (-1695.055) (-1715.747) (-1717.421) [-1704.426] -- 0:09:47
130000 -- [-1703.562] (-1702.060) (-1704.200) (-1717.805) * (-1726.017) (-1699.083) (-1711.655) [-1708.544] -- 0:09:42
Average standard deviation of split frequencies: 0.021285
131000 -- (-1696.910) (-1710.039) [-1699.480] (-1710.254) * (-1728.583) [-1704.158] (-1705.862) (-1708.493) -- 0:09:43
132000 -- (-1699.296) [-1704.847] (-1710.120) (-1706.272) * (-1698.362) (-1708.152) (-1711.974) [-1696.144] -- 0:09:45
133000 -- [-1699.726] (-1710.539) (-1710.506) (-1707.054) * (-1708.174) (-1705.112) (-1721.837) [-1704.653] -- 0:09:46
134000 -- [-1702.926] (-1706.228) (-1702.318) (-1699.434) * (-1708.276) [-1699.840] (-1704.857) (-1714.287) -- 0:09:41
135000 -- [-1703.274] (-1714.722) (-1705.508) (-1699.697) * (-1726.547) (-1696.056) [-1708.037] (-1709.868) -- 0:09:43
Average standard deviation of split frequencies: 0.018788
136000 -- (-1711.838) (-1707.085) (-1702.662) [-1692.705] * (-1708.257) [-1706.547] (-1710.216) (-1712.011) -- 0:09:44
137000 -- (-1709.629) [-1699.787] (-1709.225) (-1707.702) * [-1698.259] (-1706.312) (-1715.161) (-1714.251) -- 0:09:39
138000 -- (-1721.642) [-1699.911] (-1703.099) (-1705.623) * (-1702.155) [-1696.644] (-1720.127) (-1714.979) -- 0:09:40
139000 -- (-1698.084) (-1696.415) (-1717.278) [-1699.715] * [-1700.434] (-1706.032) (-1727.274) (-1711.606) -- 0:09:42
140000 -- (-1697.682) (-1720.443) (-1719.188) [-1712.377] * (-1701.686) [-1714.627] (-1728.870) (-1708.220) -- 0:09:37
Average standard deviation of split frequencies: 0.019057
141000 -- [-1687.406] (-1718.312) (-1715.946) (-1711.056) * (-1714.321) (-1704.938) (-1720.898) [-1709.337] -- 0:09:38
142000 -- [-1695.675] (-1714.570) (-1703.315) (-1711.043) * (-1704.289) (-1709.797) (-1712.255) [-1710.052] -- 0:09:40
143000 -- (-1700.978) (-1709.470) [-1693.799] (-1707.775) * (-1702.900) (-1699.472) (-1709.522) [-1708.815] -- 0:09:35
144000 -- [-1696.898] (-1715.207) (-1701.171) (-1696.964) * [-1705.991] (-1717.305) (-1712.474) (-1703.588) -- 0:09:36
145000 -- [-1685.153] (-1719.014) (-1711.058) (-1695.973) * (-1709.495) (-1722.074) (-1699.201) [-1707.771] -- 0:09:37
Average standard deviation of split frequencies: 0.018621
146000 -- [-1698.820] (-1730.966) (-1706.256) (-1708.639) * (-1694.245) (-1719.317) [-1688.268] (-1699.021) -- 0:09:33
147000 -- (-1691.853) (-1717.035) (-1707.211) [-1703.693] * (-1704.074) (-1713.297) [-1699.700] (-1716.499) -- 0:09:34
148000 -- [-1696.444] (-1726.630) (-1704.930) (-1708.275) * (-1718.760) [-1700.907] (-1704.156) (-1718.677) -- 0:09:35
149000 -- (-1692.017) [-1708.280] (-1711.544) (-1736.106) * (-1711.764) (-1713.213) (-1730.700) [-1707.576] -- 0:09:31
150000 -- (-1704.640) [-1710.424] (-1700.589) (-1711.877) * (-1723.014) (-1705.960) (-1707.044) [-1710.522] -- 0:09:32
Average standard deviation of split frequencies: 0.018244
151000 -- [-1701.952] (-1712.032) (-1705.269) (-1708.197) * (-1729.882) [-1706.830] (-1710.162) (-1692.794) -- 0:09:33
152000 -- (-1707.278) (-1722.041) (-1704.708) [-1700.691] * (-1712.697) [-1701.108] (-1699.540) (-1704.491) -- 0:09:29
153000 -- (-1700.625) [-1707.988] (-1718.812) (-1700.233) * [-1700.582] (-1695.167) (-1708.426) (-1705.083) -- 0:09:30
154000 -- (-1716.711) [-1705.021] (-1717.316) (-1727.749) * (-1705.948) (-1700.689) [-1688.490] (-1718.405) -- 0:09:31
155000 -- (-1713.736) [-1700.016] (-1718.172) (-1703.790) * [-1699.468] (-1697.330) (-1694.126) (-1716.009) -- 0:09:26
Average standard deviation of split frequencies: 0.019242
156000 -- (-1711.311) (-1702.113) (-1714.258) [-1705.399] * (-1696.551) (-1702.565) [-1698.074] (-1709.078) -- 0:09:28
157000 -- (-1707.080) (-1719.397) (-1705.958) [-1701.421] * [-1695.782] (-1711.407) (-1704.650) (-1709.983) -- 0:09:29
158000 -- (-1725.897) (-1703.827) [-1706.751] (-1710.686) * (-1698.059) (-1696.653) [-1692.715] (-1714.672) -- 0:09:24
159000 -- (-1712.224) [-1710.837] (-1711.287) (-1706.468) * (-1703.558) [-1703.560] (-1707.177) (-1711.776) -- 0:09:25
160000 -- (-1705.692) (-1703.085) (-1711.385) [-1695.581] * [-1703.291] (-1698.023) (-1704.867) (-1713.286) -- 0:09:27
Average standard deviation of split frequencies: 0.019373
161000 -- (-1708.367) [-1709.778] (-1721.226) (-1721.739) * (-1704.558) (-1701.372) (-1718.326) [-1691.045] -- 0:09:22
162000 -- (-1693.495) (-1718.026) (-1701.823) [-1704.792] * (-1705.626) (-1712.018) [-1697.464] (-1702.765) -- 0:09:23
163000 -- [-1699.626] (-1709.825) (-1710.795) (-1700.893) * [-1695.608] (-1704.648) (-1712.317) (-1728.577) -- 0:09:24
164000 -- (-1716.840) (-1717.112) [-1699.626] (-1701.725) * [-1704.913] (-1707.422) (-1728.503) (-1702.719) -- 0:09:20
165000 -- (-1710.298) [-1698.097] (-1711.601) (-1714.485) * (-1710.416) (-1709.017) (-1717.114) [-1703.285] -- 0:09:21
Average standard deviation of split frequencies: 0.018599
166000 -- (-1722.888) [-1708.407] (-1717.016) (-1712.109) * [-1700.942] (-1714.136) (-1707.289) (-1709.106) -- 0:09:22
167000 -- [-1703.691] (-1708.097) (-1714.741) (-1705.931) * (-1699.624) (-1714.832) (-1712.920) [-1699.588] -- 0:09:18
168000 -- (-1706.297) (-1708.496) (-1708.683) [-1692.066] * (-1700.777) (-1705.840) [-1695.377] (-1713.429) -- 0:09:19
169000 -- (-1704.037) [-1694.289] (-1715.601) (-1707.229) * (-1721.388) (-1722.520) (-1705.313) [-1706.684] -- 0:09:20
170000 -- [-1693.997] (-1710.723) (-1702.814) (-1712.549) * (-1702.395) (-1721.058) [-1700.435] (-1704.718) -- 0:09:16
Average standard deviation of split frequencies: 0.018174
171000 -- [-1697.188] (-1706.477) (-1721.773) (-1717.715) * (-1711.065) [-1705.930] (-1711.241) (-1722.844) -- 0:09:17
172000 -- [-1703.296] (-1720.576) (-1726.520) (-1716.164) * (-1700.257) (-1727.619) [-1707.498] (-1709.257) -- 0:09:18
173000 -- [-1709.337] (-1710.094) (-1709.651) (-1703.963) * (-1715.942) (-1710.430) [-1710.076] (-1729.726) -- 0:09:14
174000 -- [-1715.226] (-1701.646) (-1710.066) (-1714.253) * [-1708.829] (-1703.832) (-1697.952) (-1735.800) -- 0:09:15
175000 -- (-1698.378) [-1698.291] (-1723.017) (-1694.871) * (-1713.162) [-1695.638] (-1693.824) (-1699.519) -- 0:09:16
Average standard deviation of split frequencies: 0.017895
176000 -- [-1703.673] (-1709.774) (-1721.013) (-1702.036) * [-1699.545] (-1693.630) (-1709.275) (-1699.086) -- 0:09:12
177000 -- [-1702.178] (-1712.781) (-1705.262) (-1703.846) * [-1706.720] (-1711.441) (-1706.315) (-1714.607) -- 0:09:13
178000 -- (-1711.127) (-1710.737) [-1688.602] (-1704.380) * (-1696.657) (-1702.722) [-1705.979] (-1712.072) -- 0:09:14
179000 -- (-1709.487) (-1708.214) (-1703.675) [-1700.753] * (-1709.134) [-1693.876] (-1712.590) (-1738.075) -- 0:09:10
180000 -- [-1704.561] (-1711.342) (-1705.328) (-1697.138) * (-1710.785) (-1706.726) [-1702.181] (-1722.592) -- 0:09:11
Average standard deviation of split frequencies: 0.016730
181000 -- (-1717.001) (-1700.680) (-1726.736) [-1692.684] * (-1694.918) (-1714.291) (-1693.660) [-1699.659] -- 0:09:12
182000 -- (-1703.324) (-1715.555) (-1712.571) [-1697.062] * (-1712.449) (-1710.377) [-1699.496] (-1710.000) -- 0:09:08
183000 -- (-1697.618) (-1706.635) (-1700.920) [-1704.430] * (-1708.958) (-1710.885) [-1694.248] (-1705.843) -- 0:09:09
184000 -- (-1709.704) [-1691.129] (-1717.445) (-1706.596) * (-1707.947) (-1718.423) [-1701.699] (-1707.161) -- 0:09:09
185000 -- (-1711.593) [-1693.358] (-1714.256) (-1699.926) * (-1702.735) (-1701.134) [-1694.034] (-1718.970) -- 0:09:06
Average standard deviation of split frequencies: 0.016220
186000 -- [-1703.444] (-1695.085) (-1702.204) (-1701.552) * [-1696.586] (-1717.383) (-1716.269) (-1719.738) -- 0:09:07
187000 -- (-1717.699) (-1711.278) (-1708.178) [-1707.556] * (-1709.851) (-1714.175) [-1708.645] (-1701.536) -- 0:09:07
188000 -- (-1723.568) [-1704.141] (-1711.330) (-1703.453) * [-1700.785] (-1708.008) (-1718.213) (-1703.184) -- 0:09:04
189000 -- (-1712.830) (-1698.405) [-1703.711] (-1723.379) * (-1719.987) (-1714.044) (-1711.328) [-1705.394] -- 0:09:04
190000 -- (-1705.580) [-1703.802] (-1697.856) (-1731.993) * [-1695.479] (-1705.938) (-1710.123) (-1704.279) -- 0:09:05
Average standard deviation of split frequencies: 0.016088
191000 -- (-1709.205) (-1695.670) (-1687.118) [-1697.811] * (-1707.443) [-1700.718] (-1723.455) (-1705.940) -- 0:09:02
192000 -- (-1706.985) (-1694.346) [-1708.112] (-1708.738) * (-1700.765) (-1708.772) (-1710.504) [-1698.947] -- 0:09:02
193000 -- (-1706.667) (-1705.953) (-1703.178) [-1699.331] * [-1689.333] (-1704.919) (-1719.496) (-1717.183) -- 0:09:03
194000 -- [-1709.001] (-1719.814) (-1716.291) (-1702.297) * [-1690.620] (-1702.357) (-1719.114) (-1700.582) -- 0:09:00
195000 -- [-1697.762] (-1694.010) (-1711.317) (-1698.580) * [-1698.266] (-1715.651) (-1717.057) (-1707.987) -- 0:09:00
Average standard deviation of split frequencies: 0.015667
196000 -- (-1716.972) (-1707.872) (-1700.319) [-1706.133] * [-1689.964] (-1710.894) (-1715.269) (-1708.196) -- 0:09:01
197000 -- (-1728.986) [-1695.459] (-1690.791) (-1705.379) * (-1698.361) (-1715.940) (-1700.657) [-1701.411] -- 0:08:58
198000 -- (-1697.351) (-1703.681) (-1720.082) [-1703.442] * (-1693.619) (-1696.442) (-1735.402) [-1710.494] -- 0:08:58
199000 -- (-1704.273) [-1697.020] (-1708.132) (-1699.558) * (-1702.680) (-1700.378) [-1709.153] (-1712.927) -- 0:08:59
200000 -- (-1712.417) [-1689.392] (-1716.907) (-1701.155) * (-1697.468) [-1697.280] (-1705.156) (-1706.259) -- 0:08:56
Average standard deviation of split frequencies: 0.016546
201000 -- (-1712.428) (-1692.943) (-1693.313) [-1709.768] * [-1699.130] (-1700.581) (-1706.790) (-1706.040) -- 0:08:56
202000 -- (-1695.630) (-1704.341) (-1707.778) [-1693.966] * [-1699.568] (-1693.078) (-1708.189) (-1712.240) -- 0:08:57
203000 -- (-1711.413) (-1702.394) (-1714.262) [-1699.404] * [-1705.616] (-1698.945) (-1719.566) (-1717.607) -- 0:08:57
204000 -- (-1712.483) (-1711.314) [-1706.800] (-1705.250) * (-1716.259) (-1692.323) (-1707.943) [-1699.215] -- 0:08:54
205000 -- (-1703.968) (-1715.060) (-1707.579) [-1700.380] * (-1711.474) (-1715.052) [-1709.824] (-1728.659) -- 0:08:55
Average standard deviation of split frequencies: 0.015438
206000 -- (-1708.267) (-1714.428) (-1711.942) [-1704.236] * (-1703.969) (-1715.439) [-1706.965] (-1739.195) -- 0:08:55
207000 -- (-1707.091) (-1701.195) (-1727.939) [-1702.999] * (-1714.652) (-1708.436) [-1694.658] (-1707.537) -- 0:08:52
208000 -- (-1708.058) (-1721.093) (-1726.446) [-1699.700] * (-1705.089) (-1715.698) (-1709.636) [-1693.028] -- 0:08:53
209000 -- [-1693.924] (-1732.636) (-1721.909) (-1699.868) * [-1692.715] (-1709.851) (-1702.164) (-1702.089) -- 0:08:53
210000 -- (-1708.976) [-1706.864] (-1717.755) (-1711.667) * [-1694.168] (-1717.114) (-1697.715) (-1707.634) -- 0:08:50
Average standard deviation of split frequencies: 0.016047
211000 -- (-1701.452) (-1716.395) (-1710.537) [-1695.804] * (-1701.788) (-1707.121) (-1703.488) [-1707.023] -- 0:08:50
212000 -- [-1699.032] (-1712.941) (-1713.544) (-1718.761) * (-1716.624) (-1704.844) (-1712.789) [-1705.891] -- 0:08:51
213000 -- (-1701.685) (-1707.081) (-1720.584) [-1702.567] * (-1696.278) (-1716.381) [-1695.325] (-1715.177) -- 0:08:48
214000 -- (-1718.382) [-1703.387] (-1707.665) (-1699.039) * (-1712.306) (-1718.691) (-1707.191) [-1709.495] -- 0:08:48
215000 -- (-1718.662) (-1715.461) [-1700.430] (-1704.567) * (-1695.924) (-1719.575) [-1701.682] (-1730.935) -- 0:08:49
Average standard deviation of split frequencies: 0.015932
216000 -- (-1716.112) [-1703.284] (-1703.071) (-1702.325) * (-1693.247) (-1706.262) [-1702.951] (-1706.941) -- 0:08:46
217000 -- (-1723.707) [-1700.098] (-1706.216) (-1710.139) * [-1687.042] (-1691.241) (-1706.217) (-1711.660) -- 0:08:46
218000 -- (-1713.076) (-1702.068) [-1703.004] (-1714.135) * [-1699.095] (-1693.306) (-1711.962) (-1701.943) -- 0:08:47
219000 -- [-1702.702] (-1710.570) (-1710.580) (-1696.534) * (-1705.705) [-1700.275] (-1709.632) (-1723.510) -- 0:08:44
220000 -- [-1701.919] (-1697.231) (-1704.780) (-1716.806) * (-1693.745) [-1704.432] (-1699.911) (-1700.569) -- 0:08:44
Average standard deviation of split frequencies: 0.015102
221000 -- [-1695.057] (-1696.583) (-1703.751) (-1715.816) * [-1704.125] (-1709.693) (-1700.605) (-1707.308) -- 0:08:45
222000 -- (-1709.436) [-1692.693] (-1727.171) (-1700.890) * (-1694.039) [-1703.213] (-1715.812) (-1706.840) -- 0:08:45
223000 -- (-1698.670) (-1700.532) (-1703.726) [-1703.335] * (-1703.674) [-1701.377] (-1705.311) (-1712.929) -- 0:08:42
224000 -- (-1706.261) [-1691.686] (-1705.030) (-1713.134) * (-1706.268) (-1705.054) [-1689.137] (-1722.231) -- 0:08:43
225000 -- (-1707.904) [-1695.453] (-1723.894) (-1713.877) * (-1719.707) (-1701.365) [-1705.289] (-1716.136) -- 0:08:43
Average standard deviation of split frequencies: 0.015087
226000 -- [-1710.044] (-1701.925) (-1704.440) (-1715.965) * [-1693.514] (-1704.156) (-1705.750) (-1712.574) -- 0:08:40
227000 -- (-1707.334) (-1707.682) (-1694.371) [-1696.849] * (-1707.486) (-1715.855) [-1695.922] (-1703.763) -- 0:08:41
228000 -- (-1704.177) (-1709.037) [-1703.828] (-1702.235) * (-1699.891) (-1704.144) [-1695.582] (-1709.036) -- 0:08:41
229000 -- (-1706.268) (-1712.412) (-1705.784) [-1691.374] * (-1702.938) (-1722.158) [-1714.210] (-1729.504) -- 0:08:38
230000 -- (-1723.839) [-1700.678] (-1708.848) (-1701.359) * (-1697.128) (-1719.214) [-1706.506] (-1713.533) -- 0:08:38
Average standard deviation of split frequencies: 0.015072
231000 -- (-1719.680) (-1697.170) (-1708.031) [-1700.222] * [-1692.321] (-1707.750) (-1705.005) (-1705.414) -- 0:08:39
232000 -- (-1707.949) (-1707.166) (-1710.031) [-1700.411] * [-1695.968] (-1711.949) (-1713.464) (-1711.367) -- 0:08:36
233000 -- (-1712.538) (-1708.172) (-1714.127) [-1696.486] * (-1691.816) (-1703.815) [-1704.302] (-1706.952) -- 0:08:36
234000 -- (-1712.721) [-1697.391] (-1713.019) (-1707.697) * (-1705.780) [-1685.273] (-1719.538) (-1704.717) -- 0:08:37
235000 -- (-1703.685) [-1705.297] (-1700.310) (-1704.904) * [-1694.842] (-1698.620) (-1699.503) (-1710.088) -- 0:08:34
Average standard deviation of split frequencies: 0.014648
236000 -- (-1706.493) (-1703.174) (-1708.717) [-1699.461] * [-1698.044] (-1714.108) (-1704.903) (-1712.846) -- 0:08:34
237000 -- (-1709.630) (-1705.088) (-1710.332) [-1698.448] * (-1710.608) [-1697.256] (-1707.535) (-1707.834) -- 0:08:35
238000 -- (-1705.768) (-1701.869) (-1725.630) [-1686.578] * (-1702.794) (-1716.195) [-1703.841] (-1698.040) -- 0:08:35
239000 -- (-1723.918) (-1702.421) (-1708.274) [-1694.459] * [-1697.508] (-1702.966) (-1709.670) (-1696.298) -- 0:08:32
240000 -- (-1705.334) (-1719.578) (-1707.613) [-1696.882] * [-1708.357] (-1708.012) (-1708.051) (-1694.716) -- 0:08:33
Average standard deviation of split frequencies: 0.014732
241000 -- (-1699.726) [-1694.448] (-1717.666) (-1706.002) * (-1699.940) [-1705.661] (-1708.922) (-1700.920) -- 0:08:33
242000 -- (-1708.524) (-1692.094) [-1694.606] (-1694.364) * (-1698.548) (-1716.905) (-1723.875) [-1704.664] -- 0:08:30
243000 -- (-1703.736) (-1698.830) (-1702.353) [-1704.354] * [-1688.962] (-1700.287) (-1710.470) (-1705.315) -- 0:08:30
244000 -- (-1714.714) [-1693.952] (-1698.813) (-1724.270) * [-1696.211] (-1695.845) (-1706.762) (-1710.035) -- 0:08:31
245000 -- (-1714.011) [-1695.877] (-1719.039) (-1701.030) * (-1715.688) (-1704.950) (-1709.774) [-1705.257] -- 0:08:28
Average standard deviation of split frequencies: 0.014709
246000 -- (-1705.563) (-1719.685) (-1719.237) [-1699.133] * (-1719.604) (-1709.886) [-1709.204] (-1702.932) -- 0:08:28
247000 -- (-1700.931) (-1701.668) (-1710.217) [-1704.771] * (-1714.202) (-1697.569) (-1728.202) [-1713.590] -- 0:08:29
248000 -- [-1709.382] (-1717.978) (-1705.613) (-1710.127) * (-1722.888) [-1713.976] (-1708.494) (-1711.075) -- 0:08:26
249000 -- (-1717.562) [-1696.627] (-1732.433) (-1695.752) * [-1706.911] (-1711.363) (-1710.889) (-1699.919) -- 0:08:26
250000 -- (-1724.635) [-1703.610] (-1707.099) (-1698.346) * [-1691.197] (-1721.927) (-1709.731) (-1705.284) -- 0:08:26
Average standard deviation of split frequencies: 0.013869
251000 -- (-1705.468) (-1715.324) (-1703.933) [-1688.073] * (-1711.343) (-1706.670) [-1718.555] (-1702.872) -- 0:08:27
252000 -- (-1712.025) (-1709.558) (-1700.668) [-1688.633] * (-1709.483) [-1713.716] (-1712.365) (-1725.498) -- 0:08:24
253000 -- (-1712.146) (-1706.404) [-1698.405] (-1719.989) * (-1699.863) [-1707.505] (-1724.598) (-1722.768) -- 0:08:24
254000 -- (-1725.439) [-1708.973] (-1717.598) (-1698.139) * (-1706.534) (-1708.424) [-1707.512] (-1720.878) -- 0:08:25
255000 -- (-1722.740) (-1709.109) (-1699.163) [-1694.427] * [-1698.995] (-1707.344) (-1711.477) (-1703.041) -- 0:08:22
Average standard deviation of split frequencies: 0.013435
256000 -- (-1690.735) (-1715.061) [-1698.574] (-1698.549) * [-1701.879] (-1717.690) (-1700.124) (-1719.289) -- 0:08:22
257000 -- (-1702.693) (-1705.450) (-1710.069) [-1696.676] * [-1704.831] (-1711.478) (-1693.398) (-1703.693) -- 0:08:23
258000 -- [-1696.009] (-1697.484) (-1691.343) (-1706.235) * (-1710.328) (-1701.416) [-1699.477] (-1718.677) -- 0:08:20
259000 -- (-1706.875) (-1714.619) (-1710.446) [-1705.209] * (-1708.929) (-1723.299) [-1699.170] (-1711.762) -- 0:08:20
260000 -- (-1704.617) (-1694.816) [-1699.697] (-1710.152) * (-1709.141) (-1718.731) [-1694.327] (-1706.751) -- 0:08:20
Average standard deviation of split frequencies: 0.014202
261000 -- (-1717.591) (-1706.900) [-1685.834] (-1706.849) * [-1702.509] (-1698.493) (-1709.939) (-1713.940) -- 0:08:18
262000 -- [-1710.572] (-1702.552) (-1700.558) (-1695.680) * [-1699.166] (-1718.563) (-1700.812) (-1705.874) -- 0:08:18
263000 -- (-1715.329) (-1701.892) [-1705.974] (-1712.243) * (-1722.961) (-1723.453) [-1695.361] (-1702.529) -- 0:08:18
264000 -- (-1712.937) [-1708.486] (-1710.152) (-1704.255) * (-1708.075) (-1719.094) [-1695.379] (-1706.827) -- 0:08:16
265000 -- [-1701.362] (-1699.889) (-1694.863) (-1721.687) * (-1717.553) (-1719.816) (-1702.759) [-1689.653] -- 0:08:16
Average standard deviation of split frequencies: 0.014026
266000 -- (-1707.497) [-1694.627] (-1698.837) (-1703.984) * [-1706.190] (-1702.746) (-1703.536) (-1710.521) -- 0:08:16
267000 -- (-1702.570) (-1703.361) (-1708.137) [-1692.003] * [-1703.131] (-1719.832) (-1711.413) (-1708.929) -- 0:08:16
268000 -- (-1706.302) (-1713.368) (-1714.474) [-1699.923] * (-1716.493) [-1694.824] (-1701.148) (-1706.025) -- 0:08:14
269000 -- [-1696.796] (-1701.445) (-1703.452) (-1713.397) * (-1713.541) [-1696.017] (-1713.847) (-1698.262) -- 0:08:14
270000 -- (-1698.673) [-1694.035] (-1705.432) (-1704.477) * (-1725.239) (-1700.846) [-1706.671] (-1716.182) -- 0:08:14
Average standard deviation of split frequencies: 0.014082
271000 -- (-1697.941) (-1722.791) (-1707.094) [-1716.752] * (-1695.999) (-1719.580) [-1698.263] (-1711.469) -- 0:08:12
272000 -- [-1704.268] (-1717.043) (-1701.557) (-1714.200) * (-1697.433) [-1710.592] (-1703.844) (-1705.078) -- 0:08:12
273000 -- (-1720.400) [-1687.301] (-1700.081) (-1727.389) * (-1712.016) (-1699.330) [-1715.237] (-1731.172) -- 0:08:12
274000 -- (-1698.664) [-1699.451] (-1712.335) (-1715.140) * (-1703.864) (-1706.809) [-1701.973] (-1710.289) -- 0:08:10
275000 -- [-1699.538] (-1718.833) (-1721.137) (-1696.272) * (-1709.902) (-1718.675) [-1693.254] (-1714.083) -- 0:08:10
Average standard deviation of split frequencies: 0.014281
276000 -- (-1705.214) (-1710.099) (-1705.429) [-1704.192] * (-1703.133) (-1730.345) [-1687.837] (-1703.253) -- 0:08:10
277000 -- [-1702.758] (-1714.433) (-1696.118) (-1709.923) * [-1698.971] (-1707.123) (-1707.192) (-1709.711) -- 0:08:08
278000 -- [-1687.729] (-1701.654) (-1711.137) (-1701.418) * (-1706.696) [-1699.509] (-1704.688) (-1709.935) -- 0:08:08
279000 -- [-1698.012] (-1710.898) (-1710.903) (-1701.701) * (-1718.037) (-1711.216) [-1705.730] (-1727.984) -- 0:08:08
280000 -- (-1704.455) (-1708.042) (-1701.579) [-1701.867] * (-1706.816) (-1718.792) [-1708.552] (-1718.493) -- 0:08:06
Average standard deviation of split frequencies: 0.013763
281000 -- [-1704.302] (-1701.187) (-1713.483) (-1711.224) * (-1699.693) [-1701.079] (-1707.106) (-1725.244) -- 0:08:06
282000 -- (-1703.138) (-1710.862) [-1704.582] (-1706.481) * [-1700.666] (-1726.176) (-1699.561) (-1703.824) -- 0:08:06
283000 -- (-1697.185) (-1704.702) [-1701.625] (-1700.055) * [-1694.663] (-1722.769) (-1704.336) (-1714.257) -- 0:08:03
284000 -- (-1717.253) (-1709.760) (-1716.858) [-1698.414] * [-1701.231] (-1708.006) (-1707.864) (-1729.332) -- 0:08:04
285000 -- (-1703.166) (-1698.626) (-1704.912) [-1689.544] * (-1709.821) [-1699.265] (-1729.561) (-1726.579) -- 0:08:04
Average standard deviation of split frequencies: 0.013864
286000 -- (-1709.964) (-1704.057) (-1711.046) [-1694.761] * (-1708.237) (-1695.454) [-1707.482] (-1711.505) -- 0:08:01
287000 -- (-1704.213) (-1708.797) (-1698.544) [-1698.850] * (-1710.440) [-1704.056] (-1710.460) (-1722.403) -- 0:08:01
288000 -- [-1703.103] (-1693.409) (-1697.724) (-1708.287) * [-1705.569] (-1703.886) (-1702.473) (-1713.844) -- 0:08:02
289000 -- (-1712.681) (-1705.875) (-1711.195) [-1698.031] * [-1696.837] (-1707.816) (-1720.672) (-1713.542) -- 0:07:59
290000 -- (-1709.761) (-1708.323) (-1696.976) [-1700.153] * (-1712.480) (-1708.436) (-1699.565) [-1707.052] -- 0:07:59
Average standard deviation of split frequencies: 0.012974
291000 -- (-1708.206) (-1716.254) [-1693.271] (-1708.653) * (-1720.655) [-1695.427] (-1714.665) (-1700.250) -- 0:07:59
292000 -- (-1706.053) (-1711.171) [-1699.415] (-1709.937) * (-1713.842) (-1712.693) (-1707.261) [-1701.221] -- 0:07:57
293000 -- (-1707.133) [-1704.102] (-1706.943) (-1706.468) * [-1707.489] (-1696.377) (-1696.809) (-1716.649) -- 0:07:57
294000 -- (-1704.915) (-1692.711) (-1728.278) [-1698.184] * (-1714.056) (-1707.031) [-1691.906] (-1716.501) -- 0:07:57
295000 -- [-1692.890] (-1712.448) (-1721.926) (-1699.539) * (-1710.707) [-1707.357] (-1717.648) (-1728.847) -- 0:07:55
Average standard deviation of split frequencies: 0.012513
296000 -- [-1703.690] (-1711.442) (-1720.688) (-1703.577) * [-1698.032] (-1707.358) (-1719.402) (-1701.476) -- 0:07:55
297000 -- (-1693.660) (-1696.210) [-1704.283] (-1708.161) * [-1713.687] (-1725.604) (-1709.251) (-1725.913) -- 0:07:55
298000 -- (-1708.248) (-1703.033) (-1694.090) [-1706.421] * (-1711.698) (-1704.359) [-1695.688] (-1727.347) -- 0:07:55
299000 -- (-1713.286) (-1713.758) [-1697.950] (-1709.805) * (-1713.847) [-1697.028] (-1704.489) (-1717.639) -- 0:07:53
300000 -- (-1701.587) (-1718.963) (-1705.288) [-1702.118] * (-1704.052) [-1689.379] (-1719.896) (-1705.684) -- 0:07:53
Average standard deviation of split frequencies: 0.012319
301000 -- [-1710.405] (-1705.841) (-1707.321) (-1707.548) * (-1707.531) [-1696.391] (-1719.110) (-1716.337) -- 0:07:53
302000 -- (-1699.010) (-1713.269) (-1709.342) [-1705.135] * [-1705.175] (-1703.330) (-1717.981) (-1712.971) -- 0:07:51
303000 -- (-1722.084) (-1706.854) [-1699.492] (-1712.977) * [-1698.204] (-1703.345) (-1720.498) (-1723.374) -- 0:07:51
304000 -- (-1699.917) (-1710.027) [-1694.549] (-1712.914) * (-1689.331) [-1685.448] (-1708.262) (-1696.749) -- 0:07:49
305000 -- [-1700.491] (-1700.176) (-1694.045) (-1716.537) * (-1702.569) [-1688.375] (-1719.116) (-1706.228) -- 0:07:49
Average standard deviation of split frequencies: 0.011840
306000 -- (-1714.573) [-1686.591] (-1723.252) (-1712.605) * [-1698.632] (-1698.754) (-1698.207) (-1709.018) -- 0:07:49
307000 -- [-1700.426] (-1692.769) (-1715.364) (-1701.159) * (-1706.145) (-1699.145) (-1700.822) [-1701.414] -- 0:07:49
308000 -- (-1699.408) (-1697.957) (-1708.740) [-1705.168] * (-1704.927) [-1702.125] (-1715.427) (-1725.407) -- 0:07:47
309000 -- [-1697.320] (-1697.704) (-1710.211) (-1716.910) * (-1704.738) (-1714.621) [-1694.084] (-1702.931) -- 0:07:47
310000 -- [-1698.500] (-1705.097) (-1735.937) (-1717.888) * (-1702.428) (-1704.456) (-1708.659) [-1695.238] -- 0:07:47
Average standard deviation of split frequencies: 0.011501
311000 -- (-1702.266) (-1701.266) [-1711.344] (-1701.858) * (-1704.549) (-1709.688) [-1696.882] (-1709.335) -- 0:07:45
312000 -- [-1710.534] (-1712.569) (-1704.231) (-1702.897) * [-1692.128] (-1716.475) (-1695.189) (-1703.894) -- 0:07:45
313000 -- (-1704.865) (-1705.686) (-1718.127) [-1707.087] * (-1716.587) (-1706.199) (-1709.190) [-1702.493] -- 0:07:45
314000 -- [-1701.251] (-1710.711) (-1715.046) (-1724.133) * [-1703.419] (-1701.563) (-1716.309) (-1696.709) -- 0:07:43
315000 -- (-1714.752) (-1720.060) (-1718.767) [-1702.035] * (-1709.416) (-1712.505) (-1712.954) [-1711.173] -- 0:07:43
Average standard deviation of split frequencies: 0.011472
316000 -- (-1715.790) (-1705.924) [-1697.317] (-1720.355) * [-1698.336] (-1715.656) (-1717.645) (-1703.997) -- 0:07:43
317000 -- [-1702.837] (-1718.928) (-1708.370) (-1704.019) * [-1699.284] (-1711.277) (-1712.881) (-1694.444) -- 0:07:41
318000 -- [-1695.860] (-1726.127) (-1705.421) (-1724.022) * [-1705.685] (-1703.612) (-1701.620) (-1697.662) -- 0:07:41
319000 -- (-1715.492) (-1712.881) (-1707.622) [-1694.715] * (-1726.543) [-1695.856] (-1712.013) (-1706.579) -- 0:07:41
320000 -- [-1708.954] (-1715.857) (-1711.828) (-1712.610) * (-1714.764) [-1696.776] (-1707.622) (-1717.373) -- 0:07:39
Average standard deviation of split frequencies: 0.011566
321000 -- (-1706.486) [-1712.135] (-1716.036) (-1707.490) * [-1705.419] (-1698.659) (-1703.177) (-1716.087) -- 0:07:39
322000 -- [-1695.253] (-1710.450) (-1702.838) (-1709.480) * (-1701.071) [-1712.012] (-1721.262) (-1723.609) -- 0:07:39
323000 -- [-1700.076] (-1712.914) (-1703.810) (-1735.383) * (-1705.390) (-1725.221) [-1698.910] (-1697.538) -- 0:07:36
324000 -- (-1711.566) [-1701.756] (-1707.489) (-1715.910) * (-1704.904) (-1706.088) [-1706.922] (-1716.263) -- 0:07:36
325000 -- (-1716.330) [-1702.752] (-1711.068) (-1727.873) * (-1695.137) (-1711.526) (-1716.686) [-1710.538] -- 0:07:36
Average standard deviation of split frequencies: 0.011176
326000 -- (-1709.058) [-1712.447] (-1697.443) (-1722.349) * (-1704.464) (-1704.863) (-1701.828) [-1698.087] -- 0:07:34
327000 -- (-1715.280) (-1715.803) (-1696.784) [-1694.511] * (-1705.020) (-1704.633) [-1699.559] (-1707.623) -- 0:07:34
328000 -- [-1695.246] (-1730.270) (-1710.737) (-1696.481) * (-1696.832) (-1719.297) (-1695.114) [-1709.981] -- 0:07:34
329000 -- [-1699.412] (-1721.846) (-1709.940) (-1701.953) * (-1701.353) [-1699.726] (-1714.739) (-1709.402) -- 0:07:32
330000 -- (-1711.903) (-1702.049) [-1695.658] (-1710.412) * [-1695.284] (-1711.304) (-1717.338) (-1713.721) -- 0:07:32
Average standard deviation of split frequencies: 0.011446
331000 -- (-1715.562) (-1708.032) [-1690.424] (-1711.124) * (-1703.938) (-1713.855) (-1711.592) [-1693.508] -- 0:07:32
332000 -- (-1700.501) [-1699.502] (-1694.685) (-1717.088) * (-1704.328) [-1698.571] (-1712.225) (-1719.494) -- 0:07:30
333000 -- (-1704.915) (-1700.943) [-1684.985] (-1730.215) * [-1706.755] (-1701.159) (-1706.698) (-1708.473) -- 0:07:30
334000 -- (-1705.788) [-1697.686] (-1696.550) (-1710.916) * [-1707.936] (-1716.828) (-1711.240) (-1707.065) -- 0:07:30
335000 -- (-1715.703) (-1718.885) (-1719.926) [-1695.526] * [-1699.067] (-1710.560) (-1709.734) (-1716.251) -- 0:07:28
Average standard deviation of split frequencies: 0.011284
336000 -- (-1711.333) (-1720.039) [-1700.740] (-1711.141) * (-1719.037) [-1703.840] (-1711.444) (-1706.417) -- 0:07:28
337000 -- [-1693.767] (-1713.758) (-1722.344) (-1713.775) * (-1699.651) (-1718.393) (-1717.678) [-1694.227] -- 0:07:28
338000 -- (-1703.565) (-1708.522) (-1721.127) [-1699.495] * (-1710.808) [-1709.470] (-1716.637) (-1716.786) -- 0:07:28
339000 -- [-1711.790] (-1728.129) (-1708.800) (-1703.537) * (-1698.609) [-1696.014] (-1715.800) (-1712.512) -- 0:07:26
340000 -- (-1703.051) (-1707.181) [-1702.634] (-1704.344) * [-1697.273] (-1726.295) (-1711.919) (-1703.033) -- 0:07:26
Average standard deviation of split frequencies: 0.011169
341000 -- (-1716.840) (-1691.724) [-1695.236] (-1708.051) * [-1703.707] (-1720.592) (-1702.987) (-1715.973) -- 0:07:26
342000 -- (-1711.676) [-1706.869] (-1700.416) (-1704.775) * (-1714.603) [-1689.454] (-1698.120) (-1704.525) -- 0:07:24
343000 -- [-1708.926] (-1702.758) (-1714.379) (-1701.759) * [-1707.649] (-1698.459) (-1710.198) (-1702.516) -- 0:07:24
344000 -- [-1706.297] (-1701.225) (-1720.706) (-1709.410) * [-1703.038] (-1701.069) (-1700.639) (-1725.548) -- 0:07:24
345000 -- (-1697.515) (-1717.153) [-1703.249] (-1710.348) * (-1712.400) (-1714.125) (-1712.642) [-1702.518] -- 0:07:22
Average standard deviation of split frequencies: 0.011149
346000 -- (-1695.594) (-1711.857) (-1709.721) [-1699.679] * (-1704.238) (-1710.833) [-1702.038] (-1713.911) -- 0:07:22
347000 -- (-1707.925) (-1711.708) (-1702.258) [-1695.003] * (-1700.862) (-1717.249) (-1714.388) [-1705.324] -- 0:07:22
348000 -- (-1709.786) (-1698.476) [-1700.749] (-1699.718) * (-1697.607) [-1689.576] (-1719.554) (-1704.646) -- 0:07:20
349000 -- (-1715.196) [-1707.496] (-1718.687) (-1718.457) * (-1714.175) (-1689.213) (-1723.253) [-1695.530] -- 0:07:20
350000 -- (-1710.356) (-1723.319) [-1702.214] (-1700.559) * (-1703.864) [-1700.444] (-1711.405) (-1696.933) -- 0:07:20
Average standard deviation of split frequencies: 0.011350
351000 -- (-1702.659) (-1710.298) [-1696.904] (-1709.364) * (-1725.714) [-1698.083] (-1708.348) (-1721.785) -- 0:07:18
352000 -- (-1722.119) [-1702.221] (-1698.689) (-1710.808) * (-1723.253) [-1700.078] (-1697.268) (-1714.872) -- 0:07:18
353000 -- (-1728.245) [-1714.641] (-1699.315) (-1707.047) * (-1712.412) (-1715.874) [-1696.074] (-1707.439) -- 0:07:18
354000 -- (-1710.658) (-1706.089) (-1734.953) [-1706.918] * (-1702.086) (-1705.486) (-1712.964) [-1703.870] -- 0:07:16
355000 -- (-1719.483) [-1706.493] (-1716.030) (-1701.020) * [-1699.336] (-1707.590) (-1710.276) (-1725.251) -- 0:07:16
Average standard deviation of split frequencies: 0.011284
356000 -- [-1702.361] (-1718.556) (-1709.942) (-1707.260) * (-1722.767) [-1701.421] (-1703.044) (-1728.086) -- 0:07:15
357000 -- [-1703.846] (-1706.453) (-1704.952) (-1710.979) * (-1714.740) (-1707.719) (-1705.258) [-1704.637] -- 0:07:15
358000 -- (-1726.806) (-1695.719) (-1710.408) [-1700.108] * (-1704.187) [-1697.450] (-1716.060) (-1726.396) -- 0:07:13
359000 -- (-1716.648) (-1696.890) [-1699.273] (-1702.654) * [-1699.687] (-1707.491) (-1702.819) (-1697.583) -- 0:07:13
360000 -- [-1692.679] (-1699.733) (-1706.871) (-1700.097) * (-1704.142) [-1695.188] (-1705.763) (-1702.254) -- 0:07:13
Average standard deviation of split frequencies: 0.010956
361000 -- [-1686.705] (-1697.543) (-1702.269) (-1707.804) * (-1712.151) [-1702.672] (-1712.724) (-1701.938) -- 0:07:11
362000 -- [-1695.124] (-1701.290) (-1716.948) (-1710.757) * (-1707.932) [-1694.997] (-1728.216) (-1720.867) -- 0:07:11
363000 -- (-1699.381) [-1706.689] (-1717.089) (-1696.041) * (-1715.452) [-1700.533] (-1719.656) (-1710.991) -- 0:07:11
364000 -- (-1716.427) (-1701.735) [-1686.081] (-1699.550) * (-1716.888) (-1704.175) (-1719.873) [-1699.593] -- 0:07:09
365000 -- (-1725.887) (-1695.440) [-1703.751] (-1714.627) * (-1712.111) [-1702.651] (-1716.357) (-1701.849) -- 0:07:09
Average standard deviation of split frequencies: 0.010645
366000 -- (-1726.826) (-1697.523) (-1713.499) [-1697.978] * (-1703.933) (-1706.343) (-1712.038) [-1693.468] -- 0:07:09
367000 -- (-1703.857) (-1699.472) (-1709.837) [-1685.742] * (-1716.324) (-1708.738) (-1708.348) [-1705.640] -- 0:07:07
368000 -- [-1706.968] (-1707.632) (-1718.183) (-1697.843) * (-1709.298) (-1724.973) (-1700.328) [-1700.303] -- 0:07:07
369000 -- (-1697.306) [-1706.845] (-1715.782) (-1705.318) * (-1707.864) (-1705.447) [-1699.578] (-1706.328) -- 0:07:07
370000 -- [-1698.053] (-1722.041) (-1696.864) (-1712.293) * (-1718.424) [-1702.708] (-1705.176) (-1712.784) -- 0:07:05
Average standard deviation of split frequencies: 0.010543
371000 -- (-1706.054) (-1703.526) [-1692.112] (-1699.349) * [-1702.662] (-1709.637) (-1710.771) (-1710.562) -- 0:07:05
372000 -- (-1694.221) (-1729.031) [-1700.178] (-1709.548) * [-1706.412] (-1706.359) (-1720.986) (-1707.728) -- 0:07:05
373000 -- [-1694.395] (-1701.380) (-1704.501) (-1729.207) * [-1696.896] (-1707.830) (-1734.522) (-1699.126) -- 0:07:05
374000 -- [-1693.799] (-1706.134) (-1716.602) (-1709.736) * (-1692.432) (-1721.986) [-1701.176] (-1709.521) -- 0:07:03
375000 -- (-1705.871) [-1704.721] (-1700.293) (-1707.886) * (-1709.584) (-1705.182) [-1701.816] (-1715.692) -- 0:07:03
Average standard deviation of split frequencies: 0.010048
376000 -- [-1708.262] (-1714.619) (-1707.493) (-1699.272) * (-1707.760) [-1702.379] (-1701.988) (-1706.942) -- 0:07:03
377000 -- (-1710.525) (-1722.275) (-1711.249) [-1697.101] * (-1711.354) (-1707.395) [-1701.788] (-1712.357) -- 0:07:01
378000 -- [-1696.635] (-1707.809) (-1699.361) (-1695.276) * (-1714.827) [-1701.150] (-1709.827) (-1726.680) -- 0:07:01
379000 -- (-1710.893) (-1709.121) (-1711.422) [-1716.935] * (-1709.951) (-1719.762) [-1700.256] (-1731.349) -- 0:07:01
380000 -- (-1700.344) [-1698.699] (-1700.852) (-1721.135) * [-1698.360] (-1708.556) (-1713.734) (-1712.086) -- 0:06:59
Average standard deviation of split frequencies: 0.009959
381000 -- (-1691.983) (-1714.494) (-1717.293) [-1688.560] * [-1701.929] (-1712.437) (-1712.317) (-1700.252) -- 0:06:59
382000 -- (-1703.292) (-1699.904) [-1706.336] (-1704.104) * [-1700.234] (-1707.854) (-1723.927) (-1699.985) -- 0:06:59
383000 -- (-1704.362) [-1698.660] (-1705.855) (-1711.712) * (-1712.090) (-1716.040) [-1701.052] (-1718.964) -- 0:06:57
384000 -- (-1696.698) (-1711.657) (-1702.629) [-1706.523] * [-1710.490] (-1702.891) (-1724.660) (-1717.392) -- 0:06:57
385000 -- (-1712.342) [-1698.835] (-1702.257) (-1706.008) * (-1702.797) [-1700.516] (-1692.737) (-1720.736) -- 0:06:56
Average standard deviation of split frequencies: 0.009910
386000 -- (-1725.100) (-1710.267) (-1705.831) [-1706.263] * (-1706.050) (-1708.178) [-1700.539] (-1710.176) -- 0:06:55
387000 -- [-1701.439] (-1707.200) (-1704.945) (-1702.911) * (-1719.924) (-1701.998) [-1695.794] (-1699.055) -- 0:06:55
388000 -- (-1706.655) (-1702.037) [-1697.676] (-1704.153) * (-1694.554) (-1707.832) [-1704.703] (-1701.488) -- 0:06:54
389000 -- [-1708.187] (-1701.873) (-1716.406) (-1701.759) * (-1709.197) [-1695.014] (-1705.952) (-1701.267) -- 0:06:54
390000 -- (-1698.095) (-1701.212) (-1711.154) [-1691.934] * (-1713.953) (-1696.892) (-1709.102) [-1706.025] -- 0:06:52
Average standard deviation of split frequencies: 0.009653
391000 -- (-1715.852) [-1702.412] (-1733.168) (-1700.089) * (-1727.968) (-1697.697) [-1702.893] (-1708.925) -- 0:06:52
392000 -- (-1717.214) [-1699.403] (-1698.621) (-1715.954) * [-1697.473] (-1709.467) (-1706.404) (-1708.097) -- 0:06:52
393000 -- (-1711.378) (-1701.667) (-1698.635) [-1704.231] * (-1705.872) (-1707.152) [-1692.577] (-1718.772) -- 0:06:50
394000 -- (-1709.014) (-1697.536) (-1705.354) [-1704.918] * (-1706.271) (-1703.803) [-1695.693] (-1707.282) -- 0:06:50
395000 -- (-1707.741) (-1710.346) (-1714.388) [-1699.837] * [-1699.107] (-1714.064) (-1700.931) (-1712.909) -- 0:06:50
Average standard deviation of split frequencies: 0.009334
396000 -- (-1702.004) (-1708.341) (-1729.683) [-1692.940] * [-1693.592] (-1695.642) (-1723.354) (-1719.104) -- 0:06:48
397000 -- (-1712.947) [-1692.178] (-1718.579) (-1697.866) * [-1696.383] (-1685.627) (-1702.536) (-1706.285) -- 0:06:48
398000 -- (-1709.461) (-1699.091) (-1728.094) [-1696.145] * [-1704.435] (-1709.855) (-1719.562) (-1710.409) -- 0:06:48
399000 -- (-1716.602) [-1702.177] (-1718.222) (-1713.697) * (-1698.713) (-1697.825) (-1702.416) [-1700.887] -- 0:06:46
400000 -- [-1700.469] (-1703.845) (-1729.585) (-1720.816) * (-1696.029) (-1704.830) [-1700.379] (-1711.221) -- 0:06:46
Average standard deviation of split frequencies: 0.009412
401000 -- (-1709.525) (-1694.581) (-1711.901) [-1704.404] * (-1706.796) (-1713.478) [-1697.654] (-1701.031) -- 0:06:46
402000 -- (-1715.956) [-1699.555] (-1689.193) (-1721.940) * [-1704.620] (-1715.373) (-1713.507) (-1701.063) -- 0:06:44
403000 -- (-1707.679) (-1694.710) (-1695.101) [-1705.335] * [-1706.239] (-1712.330) (-1705.298) (-1705.889) -- 0:06:44
404000 -- (-1695.789) [-1696.424] (-1706.768) (-1711.976) * (-1707.179) [-1706.999] (-1701.847) (-1726.421) -- 0:06:44
405000 -- (-1709.164) [-1709.512] (-1696.196) (-1706.943) * (-1714.956) [-1708.168] (-1720.005) (-1723.125) -- 0:06:42
Average standard deviation of split frequencies: 0.009372
406000 -- (-1724.438) (-1719.231) (-1694.802) [-1701.195] * [-1712.853] (-1709.861) (-1706.363) (-1710.481) -- 0:06:42
407000 -- (-1713.394) [-1714.025] (-1725.091) (-1696.797) * (-1705.444) (-1704.699) (-1720.061) [-1699.274] -- 0:06:42
408000 -- (-1700.574) (-1707.624) (-1706.833) [-1703.437] * (-1708.452) [-1694.234] (-1714.309) (-1712.021) -- 0:06:40
409000 -- (-1708.572) [-1700.215] (-1708.434) (-1718.699) * (-1709.432) [-1695.995] (-1727.216) (-1705.864) -- 0:06:40
410000 -- (-1703.740) [-1697.286] (-1728.143) (-1727.337) * (-1710.424) [-1688.230] (-1703.307) (-1707.359) -- 0:06:40
Average standard deviation of split frequencies: 0.009538
411000 -- [-1705.085] (-1693.300) (-1716.548) (-1711.124) * [-1699.928] (-1711.898) (-1719.867) (-1715.652) -- 0:06:38
412000 -- (-1699.506) [-1699.046] (-1711.519) (-1705.583) * (-1701.704) [-1705.889] (-1717.831) (-1708.267) -- 0:06:38
413000 -- (-1700.541) (-1698.108) (-1706.659) [-1695.428] * [-1695.525] (-1707.396) (-1704.593) (-1708.272) -- 0:06:37
414000 -- (-1701.729) [-1702.201] (-1714.881) (-1705.926) * (-1718.233) (-1711.057) [-1704.295] (-1718.877) -- 0:06:37
415000 -- [-1707.269] (-1711.046) (-1715.352) (-1709.513) * (-1704.022) [-1691.664] (-1700.513) (-1706.144) -- 0:06:36
Average standard deviation of split frequencies: 0.009476
416000 -- (-1711.215) [-1701.297] (-1700.420) (-1709.820) * (-1712.884) [-1701.022] (-1704.623) (-1708.585) -- 0:06:35
417000 -- (-1711.779) (-1719.095) (-1711.056) [-1703.154] * (-1707.264) [-1697.551] (-1720.829) (-1701.054) -- 0:06:35
418000 -- (-1711.057) (-1719.655) (-1720.276) [-1700.495] * (-1703.639) (-1705.974) (-1715.068) [-1702.181] -- 0:06:34
419000 -- (-1715.399) [-1697.038] (-1721.947) (-1704.075) * (-1709.545) (-1702.511) (-1734.318) [-1697.845] -- 0:06:33
420000 -- (-1705.366) [-1697.715] (-1720.083) (-1704.825) * (-1700.592) (-1711.237) (-1705.033) [-1696.184] -- 0:06:33
Average standard deviation of split frequencies: 0.009080
421000 -- (-1720.226) (-1709.149) (-1708.631) [-1700.060] * [-1704.442] (-1705.079) (-1709.644) (-1699.695) -- 0:06:31
422000 -- [-1697.232] (-1713.254) (-1703.595) (-1700.460) * [-1703.597] (-1714.994) (-1703.167) (-1717.116) -- 0:06:31
423000 -- (-1714.560) (-1701.527) [-1708.273] (-1710.101) * [-1701.675] (-1739.035) (-1700.152) (-1698.633) -- 0:06:31
424000 -- (-1714.070) [-1699.301] (-1700.176) (-1703.600) * (-1712.123) [-1699.533] (-1724.399) (-1706.023) -- 0:06:29
425000 -- (-1728.671) (-1696.848) (-1703.248) [-1699.130] * [-1700.523] (-1702.478) (-1726.330) (-1709.139) -- 0:06:29
Average standard deviation of split frequencies: 0.009270
426000 -- [-1704.426] (-1698.991) (-1693.817) (-1714.900) * [-1696.041] (-1702.853) (-1703.048) (-1712.774) -- 0:06:29
427000 -- [-1696.300] (-1706.687) (-1708.946) (-1714.550) * (-1700.234) [-1701.100] (-1715.059) (-1694.973) -- 0:06:27
428000 -- (-1701.159) (-1717.938) [-1710.194] (-1708.485) * (-1716.611) [-1706.981] (-1725.862) (-1699.896) -- 0:06:27
429000 -- [-1698.210] (-1710.838) (-1706.531) (-1722.432) * [-1706.776] (-1703.669) (-1710.961) (-1713.099) -- 0:06:27
430000 -- [-1697.002] (-1709.920) (-1699.352) (-1727.461) * (-1712.031) (-1716.054) [-1695.655] (-1697.709) -- 0:06:25
Average standard deviation of split frequencies: 0.009312
431000 -- [-1702.322] (-1701.463) (-1707.495) (-1719.615) * [-1707.074] (-1713.064) (-1710.087) (-1702.514) -- 0:06:25
432000 -- [-1690.755] (-1718.366) (-1700.536) (-1703.070) * (-1705.572) (-1712.073) (-1706.003) [-1693.432] -- 0:06:25
433000 -- (-1702.830) (-1713.992) (-1728.848) [-1708.649] * [-1697.635] (-1710.017) (-1702.803) (-1702.748) -- 0:06:23
434000 -- [-1705.310] (-1711.685) (-1718.241) (-1707.773) * [-1702.340] (-1709.957) (-1700.588) (-1716.224) -- 0:06:23
435000 -- (-1716.986) [-1703.814] (-1718.892) (-1705.116) * (-1692.446) (-1712.793) [-1700.436] (-1709.973) -- 0:06:23
Average standard deviation of split frequencies: 0.009496
436000 -- [-1709.313] (-1709.163) (-1735.011) (-1706.915) * [-1689.512] (-1717.545) (-1706.550) (-1704.164) -- 0:06:21
437000 -- (-1706.026) (-1693.211) [-1692.979] (-1702.799) * [-1698.112] (-1702.747) (-1719.477) (-1701.178) -- 0:06:21
438000 -- (-1725.219) [-1696.848] (-1709.677) (-1709.308) * (-1706.854) (-1706.224) (-1699.494) [-1709.059] -- 0:06:19
439000 -- (-1724.997) (-1703.891) (-1713.165) [-1701.621] * (-1713.977) (-1718.011) (-1712.306) [-1700.643] -- 0:06:19
440000 -- (-1711.400) (-1707.948) (-1699.223) [-1691.922] * (-1721.730) (-1707.599) [-1700.394] (-1714.490) -- 0:06:19
Average standard deviation of split frequencies: 0.009282
441000 -- (-1741.438) (-1712.856) (-1710.746) [-1690.570] * (-1719.965) [-1694.031] (-1703.573) (-1702.367) -- 0:06:19
442000 -- (-1709.008) [-1699.887] (-1706.127) (-1701.328) * (-1728.352) [-1694.453] (-1700.724) (-1718.501) -- 0:06:17
443000 -- (-1722.663) [-1703.675] (-1715.476) (-1694.228) * [-1710.844] (-1710.473) (-1694.179) (-1706.342) -- 0:06:17
444000 -- (-1731.194) (-1709.086) (-1720.596) [-1699.594] * (-1710.648) (-1697.397) [-1710.957] (-1706.802) -- 0:06:16
445000 -- (-1717.628) [-1706.129] (-1707.518) (-1723.145) * (-1709.804) (-1716.403) [-1691.037] (-1704.862) -- 0:06:15
Average standard deviation of split frequencies: 0.009109
446000 -- (-1707.384) (-1713.297) [-1697.689] (-1715.083) * [-1691.716] (-1717.838) (-1697.437) (-1694.118) -- 0:06:15
447000 -- (-1706.118) (-1702.725) (-1709.925) [-1707.136] * (-1706.651) (-1717.178) [-1702.192] (-1733.775) -- 0:06:14
448000 -- (-1704.930) (-1697.776) [-1705.736] (-1718.413) * [-1698.746] (-1710.340) (-1706.046) (-1725.046) -- 0:06:13
449000 -- (-1710.158) (-1706.119) (-1703.848) [-1701.774] * (-1701.063) (-1708.784) [-1700.066] (-1708.645) -- 0:06:13
450000 -- (-1696.934) (-1714.570) [-1701.722] (-1703.531) * (-1711.922) (-1703.581) [-1698.765] (-1701.432) -- 0:06:12
Average standard deviation of split frequencies: 0.009608
451000 -- (-1706.961) (-1726.087) (-1707.219) [-1687.295] * [-1713.872] (-1715.028) (-1707.003) (-1715.000) -- 0:06:11
452000 -- (-1717.627) [-1713.183] (-1712.790) (-1696.055) * (-1719.424) (-1702.130) [-1702.375] (-1708.748) -- 0:06:10
453000 -- (-1715.712) (-1719.519) (-1708.094) [-1703.723] * (-1715.994) (-1704.113) [-1695.374] (-1706.046) -- 0:06:10
454000 -- (-1706.394) [-1692.695] (-1726.528) (-1709.700) * [-1710.366] (-1720.328) (-1701.784) (-1711.230) -- 0:06:09
455000 -- [-1692.903] (-1702.218) (-1715.454) (-1715.441) * (-1717.072) (-1708.221) [-1707.545] (-1702.166) -- 0:06:08
Average standard deviation of split frequencies: 0.009589
456000 -- [-1696.997] (-1716.279) (-1703.836) (-1709.741) * (-1706.480) (-1697.215) (-1709.450) [-1699.230] -- 0:06:08
457000 -- (-1712.213) (-1713.555) [-1689.148] (-1715.569) * (-1711.453) (-1711.420) (-1700.454) [-1688.385] -- 0:06:07
458000 -- (-1702.419) (-1708.728) [-1695.971] (-1706.526) * [-1701.025] (-1716.225) (-1708.899) (-1705.368) -- 0:06:06
459000 -- (-1717.933) (-1703.481) [-1703.877] (-1709.672) * (-1695.275) (-1724.207) (-1712.859) [-1715.662] -- 0:06:06
460000 -- (-1721.710) (-1715.948) [-1701.412] (-1711.829) * (-1714.328) (-1718.449) [-1707.929] (-1697.490) -- 0:06:05
Average standard deviation of split frequencies: 0.009462
461000 -- [-1707.709] (-1712.107) (-1700.096) (-1722.822) * [-1691.942] (-1719.793) (-1707.595) (-1700.856) -- 0:06:04
462000 -- (-1702.552) (-1711.669) [-1708.536] (-1714.643) * [-1699.842] (-1724.416) (-1704.855) (-1700.364) -- 0:06:04
463000 -- (-1724.601) (-1699.512) [-1698.481] (-1717.322) * (-1714.878) (-1709.057) (-1720.031) [-1691.611] -- 0:06:03
464000 -- (-1715.831) (-1713.916) [-1705.693] (-1702.674) * [-1688.134] (-1704.437) (-1708.783) (-1708.039) -- 0:06:02
465000 -- (-1710.857) (-1717.902) [-1695.923] (-1711.667) * (-1695.249) (-1708.770) [-1711.273] (-1724.805) -- 0:06:02
Average standard deviation of split frequencies: 0.009532
466000 -- [-1694.785] (-1717.324) (-1716.672) (-1702.168) * (-1700.514) (-1713.641) [-1708.906] (-1708.747) -- 0:06:02
467000 -- (-1696.891) (-1715.060) (-1710.632) [-1700.027] * [-1695.342] (-1705.751) (-1706.594) (-1710.490) -- 0:06:00
468000 -- (-1707.266) (-1711.141) (-1715.398) [-1691.167] * [-1690.144] (-1708.281) (-1720.909) (-1704.519) -- 0:06:00
469000 -- [-1701.018] (-1711.538) (-1708.874) (-1714.007) * (-1696.549) (-1708.405) (-1711.522) [-1700.384] -- 0:06:00
470000 -- (-1693.077) [-1699.975] (-1703.665) (-1706.148) * (-1711.992) (-1711.904) [-1697.276] (-1699.338) -- 0:05:58
Average standard deviation of split frequencies: 0.009898
471000 -- (-1718.159) (-1709.120) (-1719.481) [-1695.665] * (-1723.750) (-1720.178) (-1714.992) [-1696.483] -- 0:05:58
472000 -- (-1705.379) [-1695.621] (-1713.920) (-1701.056) * (-1720.065) (-1704.791) (-1713.317) [-1695.273] -- 0:05:57
473000 -- [-1708.273] (-1703.010) (-1715.211) (-1711.245) * (-1712.800) (-1726.341) [-1702.097] (-1695.923) -- 0:05:56
474000 -- (-1712.043) (-1705.830) (-1709.572) [-1700.380] * (-1703.791) (-1723.419) [-1696.100] (-1709.252) -- 0:05:56
475000 -- (-1701.840) (-1715.871) [-1692.171] (-1707.742) * (-1716.797) (-1710.397) (-1708.715) [-1686.845] -- 0:05:55
Average standard deviation of split frequencies: 0.009598
476000 -- [-1703.163] (-1710.879) (-1718.103) (-1694.021) * [-1698.748] (-1727.205) (-1705.759) (-1708.119) -- 0:05:54
477000 -- [-1714.082] (-1696.849) (-1721.561) (-1722.107) * [-1696.150] (-1719.588) (-1719.121) (-1705.035) -- 0:05:54
478000 -- (-1733.978) [-1693.152] (-1703.024) (-1701.261) * [-1692.519] (-1709.832) (-1716.343) (-1695.732) -- 0:05:53
479000 -- (-1713.819) (-1712.849) [-1706.532] (-1712.770) * [-1698.762] (-1706.873) (-1718.823) (-1704.192) -- 0:05:53
480000 -- (-1706.228) (-1708.330) [-1700.628] (-1706.205) * (-1698.841) (-1699.952) (-1703.888) [-1695.867] -- 0:05:52
Average standard deviation of split frequencies: 0.009750
481000 -- (-1712.032) [-1697.923] (-1711.506) (-1713.037) * (-1699.706) (-1719.371) [-1697.141] (-1711.318) -- 0:05:51
482000 -- (-1710.864) [-1695.071] (-1721.126) (-1722.026) * (-1708.506) (-1694.422) [-1699.557] (-1714.165) -- 0:05:51
483000 -- (-1705.505) [-1706.136] (-1702.560) (-1711.574) * (-1712.661) [-1699.968] (-1696.072) (-1710.458) -- 0:05:50
484000 -- [-1715.746] (-1699.341) (-1705.440) (-1711.500) * (-1706.391) (-1710.659) [-1709.325] (-1708.712) -- 0:05:49
485000 -- [-1719.429] (-1702.723) (-1710.786) (-1706.729) * (-1710.485) (-1718.667) (-1696.362) [-1696.932] -- 0:05:49
Average standard deviation of split frequencies: 0.009503
486000 -- (-1699.638) (-1699.559) (-1707.637) [-1697.858] * (-1707.505) [-1706.783] (-1704.634) (-1699.572) -- 0:05:47
487000 -- [-1697.067] (-1713.490) (-1701.543) (-1709.432) * [-1700.816] (-1728.171) (-1711.064) (-1705.486) -- 0:05:47
488000 -- (-1713.367) [-1716.785] (-1702.492) (-1715.035) * (-1696.450) [-1694.966] (-1715.136) (-1709.611) -- 0:05:47
489000 -- (-1716.714) (-1695.683) [-1709.367] (-1722.085) * (-1713.280) [-1714.306] (-1703.601) (-1716.753) -- 0:05:45
490000 -- (-1703.778) [-1703.902] (-1720.258) (-1709.233) * (-1708.786) [-1702.036] (-1716.548) (-1701.619) -- 0:05:45
Average standard deviation of split frequencies: 0.009092
491000 -- [-1720.263] (-1707.619) (-1727.214) (-1711.725) * (-1714.049) (-1702.748) (-1715.384) [-1697.269] -- 0:05:45
492000 -- (-1706.238) [-1701.176] (-1710.916) (-1711.180) * (-1714.813) (-1705.392) [-1704.685] (-1704.426) -- 0:05:43
493000 -- [-1697.957] (-1700.539) (-1703.891) (-1715.983) * (-1711.544) (-1699.261) (-1708.756) [-1690.824] -- 0:05:43
494000 -- (-1696.974) [-1689.012] (-1714.442) (-1728.014) * (-1704.610) [-1687.197] (-1705.931) (-1701.664) -- 0:05:43
495000 -- (-1709.797) [-1696.117] (-1720.249) (-1717.047) * [-1702.031] (-1706.047) (-1701.685) (-1714.918) -- 0:05:41
Average standard deviation of split frequencies: 0.009008
496000 -- (-1703.579) [-1689.049] (-1715.235) (-1708.674) * (-1699.291) [-1699.796] (-1716.058) (-1714.910) -- 0:05:41
497000 -- [-1705.423] (-1702.975) (-1698.793) (-1697.665) * (-1709.777) [-1696.037] (-1709.994) (-1709.306) -- 0:05:41
498000 -- (-1700.656) (-1712.294) (-1695.502) [-1696.802] * (-1698.121) [-1714.639] (-1690.393) (-1729.237) -- 0:05:40
499000 -- (-1704.117) (-1691.463) (-1706.793) [-1696.206] * [-1697.234] (-1720.050) (-1708.118) (-1708.020) -- 0:05:39
500000 -- (-1705.117) [-1702.215] (-1706.693) (-1733.535) * (-1727.624) (-1701.102) (-1712.622) [-1696.158] -- 0:05:39
Average standard deviation of split frequencies: 0.008540
501000 -- (-1719.249) (-1701.666) [-1705.691] (-1711.115) * (-1707.385) [-1692.422] (-1715.427) (-1705.354) -- 0:05:38
502000 -- (-1704.383) (-1703.778) (-1699.170) [-1697.497] * (-1719.930) (-1706.318) (-1708.247) [-1708.277] -- 0:05:37
503000 -- (-1712.983) (-1704.590) (-1694.328) [-1707.762] * (-1714.003) (-1714.957) (-1697.474) [-1698.292] -- 0:05:36
504000 -- [-1699.048] (-1713.419) (-1710.047) (-1703.447) * (-1710.571) (-1722.261) [-1705.393] (-1714.244) -- 0:05:36
505000 -- [-1704.026] (-1745.666) (-1704.860) (-1706.038) * (-1695.541) (-1716.609) [-1698.868] (-1707.562) -- 0:05:35
Average standard deviation of split frequencies: 0.008621
506000 -- [-1691.112] (-1712.204) (-1707.591) (-1706.386) * (-1703.780) (-1713.078) (-1708.940) [-1703.578] -- 0:05:34
507000 -- (-1700.552) (-1720.587) [-1701.444] (-1713.264) * (-1699.642) (-1693.631) (-1711.695) [-1710.040] -- 0:05:34
508000 -- [-1705.903] (-1728.708) (-1701.844) (-1721.610) * [-1704.231] (-1712.182) (-1722.287) (-1710.737) -- 0:05:33
509000 -- (-1724.243) (-1723.161) [-1696.129] (-1705.644) * (-1704.699) (-1706.997) (-1729.293) [-1706.518] -- 0:05:32
510000 -- (-1707.929) (-1705.924) [-1699.657] (-1723.595) * (-1719.792) (-1703.638) [-1701.530] (-1698.630) -- 0:05:32
Average standard deviation of split frequencies: 0.008730
511000 -- (-1707.114) [-1703.162] (-1726.334) (-1724.846) * (-1702.636) (-1702.720) [-1702.687] (-1718.003) -- 0:05:31
512000 -- (-1714.693) (-1709.725) [-1695.493] (-1725.278) * [-1698.655] (-1700.879) (-1720.400) (-1713.488) -- 0:05:30
513000 -- [-1713.280] (-1702.698) (-1721.535) (-1720.481) * (-1705.714) [-1710.469] (-1719.898) (-1719.020) -- 0:05:30
514000 -- (-1705.665) (-1718.201) (-1722.329) [-1712.440] * (-1702.036) (-1708.241) [-1703.767] (-1718.887) -- 0:05:29
515000 -- (-1714.383) (-1706.215) (-1713.717) [-1698.749] * (-1698.805) (-1697.690) [-1691.282] (-1708.781) -- 0:05:28
Average standard deviation of split frequencies: 0.009030
516000 -- [-1695.624] (-1702.028) (-1708.300) (-1706.879) * [-1697.798] (-1695.461) (-1708.049) (-1694.215) -- 0:05:28
517000 -- (-1707.957) [-1698.379] (-1696.262) (-1710.239) * (-1709.595) (-1705.081) [-1696.391] (-1702.847) -- 0:05:27
518000 -- (-1704.561) (-1711.071) (-1704.528) [-1702.774] * [-1714.673] (-1722.776) (-1715.973) (-1715.929) -- 0:05:26
519000 -- (-1720.101) (-1716.337) (-1697.077) [-1714.095] * (-1713.109) [-1710.119] (-1721.876) (-1710.709) -- 0:05:26
520000 -- [-1701.339] (-1702.329) (-1713.201) (-1710.410) * (-1702.461) [-1706.795] (-1710.827) (-1715.830) -- 0:05:25
Average standard deviation of split frequencies: 0.008562
521000 -- (-1697.747) [-1694.622] (-1720.652) (-1711.765) * [-1696.352] (-1716.516) (-1717.527) (-1716.546) -- 0:05:24
522000 -- (-1699.229) [-1700.147] (-1710.988) (-1720.777) * [-1695.339] (-1703.938) (-1727.542) (-1707.132) -- 0:05:24
523000 -- (-1710.064) (-1708.505) [-1696.994] (-1694.000) * (-1694.723) (-1710.265) (-1699.886) [-1705.293] -- 0:05:23
524000 -- [-1714.985] (-1710.388) (-1712.922) (-1694.316) * (-1721.717) [-1702.676] (-1698.248) (-1721.673) -- 0:05:22
525000 -- (-1687.730) (-1737.774) (-1704.731) [-1709.239] * (-1709.675) [-1707.871] (-1706.308) (-1702.514) -- 0:05:22
Average standard deviation of split frequencies: 0.007826
526000 -- [-1701.681] (-1711.724) (-1721.067) (-1700.630) * (-1709.323) [-1703.072] (-1692.081) (-1702.671) -- 0:05:21
527000 -- [-1702.978] (-1714.700) (-1698.915) (-1710.222) * [-1707.821] (-1711.177) (-1713.169) (-1705.530) -- 0:05:20
528000 -- (-1708.168) (-1711.682) (-1696.893) [-1704.603] * [-1713.018] (-1716.948) (-1697.123) (-1702.368) -- 0:05:20
529000 -- [-1694.386] (-1710.447) (-1704.900) (-1698.564) * (-1710.089) (-1718.045) (-1704.794) [-1703.185] -- 0:05:19
530000 -- (-1715.532) (-1703.890) (-1710.926) [-1703.834] * (-1711.123) (-1706.952) [-1700.399] (-1723.221) -- 0:05:18
Average standard deviation of split frequencies: 0.008008
531000 -- (-1709.330) [-1697.530] (-1712.556) (-1719.921) * (-1706.974) (-1704.051) [-1703.099] (-1717.434) -- 0:05:17
532000 -- (-1701.033) [-1696.511] (-1715.989) (-1710.607) * [-1708.801] (-1704.759) (-1707.974) (-1711.907) -- 0:05:17
533000 -- (-1703.967) (-1694.096) (-1710.052) [-1704.962] * (-1706.326) (-1699.014) [-1698.065] (-1713.781) -- 0:05:16
534000 -- (-1717.106) (-1716.176) [-1694.172] (-1697.641) * (-1720.399) [-1699.123] (-1705.552) (-1701.624) -- 0:05:15
535000 -- (-1720.476) [-1701.677] (-1691.441) (-1702.930) * (-1730.262) (-1705.489) [-1709.288] (-1706.004) -- 0:05:15
Average standard deviation of split frequencies: 0.008418
536000 -- (-1700.989) (-1706.576) (-1720.060) [-1699.386] * [-1699.055] (-1724.992) (-1706.369) (-1707.301) -- 0:05:14
537000 -- (-1701.436) (-1707.356) [-1698.198] (-1715.435) * [-1701.042] (-1707.294) (-1704.080) (-1709.834) -- 0:05:13
538000 -- (-1695.584) (-1698.880) [-1696.550] (-1700.984) * (-1704.544) (-1696.604) (-1710.314) [-1698.680] -- 0:05:13
539000 -- (-1714.820) (-1697.238) (-1695.049) [-1704.971] * (-1717.776) [-1700.990] (-1702.497) (-1699.064) -- 0:05:13
540000 -- (-1705.396) [-1689.558] (-1706.294) (-1720.147) * (-1700.337) (-1711.902) (-1700.330) [-1691.556] -- 0:05:11
Average standard deviation of split frequencies: 0.008466
541000 -- (-1708.709) (-1695.848) [-1706.038] (-1719.496) * (-1703.882) (-1705.263) (-1706.668) [-1688.773] -- 0:05:11
542000 -- (-1706.466) [-1703.544] (-1716.829) (-1709.324) * (-1707.542) (-1703.606) [-1701.216] (-1701.338) -- 0:05:10
543000 -- (-1706.071) (-1701.789) (-1712.805) [-1695.842] * (-1707.458) (-1734.216) (-1692.417) [-1700.525] -- 0:05:09
544000 -- (-1703.046) (-1707.126) (-1701.001) [-1694.958] * (-1711.662) (-1702.025) [-1702.798] (-1723.674) -- 0:05:09
545000 -- (-1705.353) (-1711.058) (-1714.250) [-1690.483] * (-1703.069) (-1711.262) (-1712.595) [-1707.737] -- 0:05:08
Average standard deviation of split frequencies: 0.008269
546000 -- [-1705.007] (-1710.781) (-1709.316) (-1713.321) * (-1704.915) (-1700.797) [-1700.810] (-1702.927) -- 0:05:07
547000 -- [-1706.360] (-1692.809) (-1725.379) (-1706.521) * [-1701.327] (-1714.319) (-1697.629) (-1721.628) -- 0:05:07
548000 -- (-1700.753) [-1704.632] (-1707.604) (-1716.545) * [-1689.862] (-1730.146) (-1695.123) (-1706.112) -- 0:05:06
549000 -- [-1687.841] (-1703.848) (-1715.898) (-1705.079) * [-1697.335] (-1720.970) (-1696.639) (-1703.104) -- 0:05:05
550000 -- (-1710.938) [-1693.681] (-1707.619) (-1722.850) * (-1711.882) (-1709.093) (-1706.087) [-1710.672] -- 0:05:05
Average standard deviation of split frequencies: 0.008500
551000 -- (-1700.497) [-1706.538] (-1711.531) (-1697.158) * [-1706.367] (-1707.361) (-1714.846) (-1707.130) -- 0:05:04
552000 -- (-1706.262) [-1707.953] (-1723.209) (-1716.014) * [-1697.107] (-1716.600) (-1714.562) (-1706.254) -- 0:05:03
553000 -- (-1703.393) [-1699.773] (-1725.151) (-1709.839) * [-1700.571] (-1709.400) (-1720.617) (-1708.633) -- 0:05:03
554000 -- [-1711.660] (-1708.791) (-1714.855) (-1707.040) * (-1705.382) (-1710.139) [-1707.697] (-1713.475) -- 0:05:02
555000 -- (-1712.699) [-1699.187] (-1708.155) (-1699.996) * (-1704.195) [-1705.470] (-1701.779) (-1718.461) -- 0:05:01
Average standard deviation of split frequencies: 0.008407
556000 -- (-1709.382) [-1705.013] (-1698.684) (-1702.322) * (-1712.404) (-1705.938) [-1693.573] (-1704.619) -- 0:05:01
557000 -- (-1718.000) (-1703.947) (-1720.734) [-1701.057] * (-1693.687) (-1707.470) [-1689.545] (-1731.884) -- 0:05:00
558000 -- (-1716.306) [-1699.401] (-1718.546) (-1704.816) * [-1701.779] (-1715.991) (-1694.513) (-1711.135) -- 0:04:59
559000 -- [-1703.052] (-1709.638) (-1718.049) (-1711.588) * (-1701.846) (-1713.095) [-1709.934] (-1715.119) -- 0:04:58
560000 -- (-1706.869) (-1702.886) (-1725.088) [-1700.269] * (-1701.990) [-1698.049] (-1714.174) (-1724.129) -- 0:04:58
Average standard deviation of split frequencies: 0.008627
561000 -- (-1722.670) [-1698.665] (-1707.474) (-1711.781) * (-1708.467) (-1704.108) (-1700.409) [-1705.838] -- 0:04:57
562000 -- [-1694.520] (-1699.655) (-1728.863) (-1699.199) * (-1712.822) (-1705.555) [-1697.164] (-1708.391) -- 0:04:56
563000 -- [-1686.796] (-1703.021) (-1707.986) (-1706.513) * [-1700.286] (-1717.129) (-1706.716) (-1701.762) -- 0:04:56
564000 -- (-1704.861) (-1701.207) (-1712.339) [-1705.342] * (-1697.708) (-1719.203) [-1701.970] (-1712.356) -- 0:04:55
565000 -- (-1712.114) [-1706.595] (-1723.448) (-1700.904) * [-1701.628] (-1713.569) (-1705.573) (-1713.650) -- 0:04:54
Average standard deviation of split frequencies: 0.008606
566000 -- (-1708.487) (-1715.527) [-1709.098] (-1705.184) * [-1698.405] (-1709.672) (-1703.285) (-1718.805) -- 0:04:54
567000 -- (-1721.183) (-1709.495) (-1714.622) [-1692.456] * [-1699.585] (-1707.453) (-1702.634) (-1719.986) -- 0:04:53
568000 -- [-1696.277] (-1716.604) (-1703.301) (-1709.425) * (-1710.225) [-1700.184] (-1710.943) (-1710.295) -- 0:04:52
569000 -- (-1720.978) (-1699.480) [-1710.737] (-1713.588) * [-1702.352] (-1703.575) (-1705.411) (-1718.693) -- 0:04:52
570000 -- (-1699.209) [-1692.363] (-1713.153) (-1727.057) * (-1697.412) (-1708.001) (-1705.819) [-1708.163] -- 0:04:51
Average standard deviation of split frequencies: 0.008589
571000 -- [-1696.409] (-1711.230) (-1715.227) (-1738.842) * (-1730.037) (-1712.175) (-1702.939) [-1706.524] -- 0:04:50
572000 -- [-1702.027] (-1700.455) (-1713.181) (-1710.915) * (-1731.275) [-1703.016] (-1700.907) (-1704.668) -- 0:04:50
573000 -- (-1704.697) (-1710.625) (-1699.463) [-1705.847] * (-1704.605) (-1702.004) [-1707.783] (-1703.705) -- 0:04:49
574000 -- [-1699.322] (-1708.573) (-1707.589) (-1707.658) * [-1697.115] (-1721.527) (-1708.994) (-1703.600) -- 0:04:48
575000 -- (-1725.274) (-1701.653) (-1699.745) [-1705.880] * (-1700.471) [-1720.579] (-1711.882) (-1693.246) -- 0:04:48
Average standard deviation of split frequencies: 0.008362
576000 -- (-1706.787) (-1704.157) [-1711.369] (-1712.047) * (-1702.766) (-1699.870) [-1698.772] (-1706.204) -- 0:04:47
577000 -- (-1689.927) (-1721.593) (-1718.712) [-1704.011] * [-1698.016] (-1711.130) (-1705.811) (-1701.194) -- 0:04:46
578000 -- (-1690.434) [-1703.395] (-1705.914) (-1704.868) * [-1701.628] (-1709.784) (-1721.911) (-1704.993) -- 0:04:46
579000 -- (-1702.691) (-1707.233) (-1708.270) [-1697.707] * (-1711.890) (-1703.930) (-1719.047) [-1692.919] -- 0:04:45
580000 -- (-1712.653) (-1710.427) [-1709.399] (-1713.624) * [-1706.978] (-1700.335) (-1712.421) (-1697.446) -- 0:04:44
Average standard deviation of split frequencies: 0.008724
581000 -- [-1692.918] (-1711.184) (-1709.449) (-1717.549) * (-1718.682) (-1711.978) [-1705.405] (-1703.284) -- 0:04:44
582000 -- [-1689.331] (-1713.053) (-1722.308) (-1700.367) * (-1694.229) (-1708.503) [-1712.112] (-1705.734) -- 0:04:42
583000 -- [-1699.840] (-1718.708) (-1704.782) (-1707.699) * (-1693.786) [-1707.543] (-1703.871) (-1700.858) -- 0:04:42
584000 -- [-1696.640] (-1698.344) (-1703.493) (-1701.672) * [-1700.518] (-1714.381) (-1713.608) (-1692.111) -- 0:04:42
585000 -- [-1693.066] (-1694.447) (-1707.697) (-1695.695) * (-1705.893) [-1697.605] (-1697.731) (-1701.264) -- 0:04:41
Average standard deviation of split frequencies: 0.008861
586000 -- [-1703.661] (-1708.383) (-1708.901) (-1702.675) * (-1726.584) (-1709.761) (-1697.343) [-1693.845] -- 0:04:40
587000 -- [-1697.693] (-1713.562) (-1700.021) (-1708.357) * (-1725.138) [-1700.797] (-1704.195) (-1701.415) -- 0:04:40
588000 -- [-1706.639] (-1704.438) (-1715.700) (-1698.097) * (-1708.790) [-1708.769] (-1709.864) (-1703.466) -- 0:04:39
589000 -- (-1712.536) [-1702.629] (-1706.639) (-1694.293) * (-1721.183) (-1711.831) [-1706.552] (-1701.098) -- 0:04:38
590000 -- [-1710.581] (-1721.139) (-1710.943) (-1699.685) * (-1713.766) (-1701.792) [-1695.243] (-1704.101) -- 0:04:37
Average standard deviation of split frequencies: 0.009010
591000 -- (-1704.219) (-1703.150) (-1721.125) [-1701.016] * (-1699.108) (-1698.375) (-1714.414) [-1703.751] -- 0:04:37
592000 -- (-1702.547) (-1698.517) [-1693.751] (-1716.078) * (-1707.333) (-1721.661) (-1708.589) [-1701.673] -- 0:04:36
593000 -- (-1696.323) (-1708.057) [-1703.379] (-1713.646) * [-1702.858] (-1708.807) (-1715.737) (-1700.891) -- 0:04:35
594000 -- (-1713.155) (-1713.469) (-1697.763) [-1699.869] * (-1710.870) (-1714.432) [-1699.034] (-1720.937) -- 0:04:35
595000 -- (-1702.624) (-1721.401) [-1710.986] (-1707.943) * (-1708.791) [-1703.298] (-1707.088) (-1709.705) -- 0:04:34
Average standard deviation of split frequencies: 0.008542
596000 -- (-1696.441) (-1715.369) [-1709.779] (-1706.072) * (-1708.928) [-1693.888] (-1712.229) (-1708.708) -- 0:04:33
597000 -- [-1706.853] (-1725.807) (-1708.899) (-1696.397) * (-1704.364) [-1704.656] (-1713.070) (-1704.005) -- 0:04:33
598000 -- (-1692.299) (-1712.715) [-1698.732] (-1701.653) * [-1706.060] (-1696.697) (-1706.057) (-1706.504) -- 0:04:32
599000 -- (-1701.124) [-1709.917] (-1699.452) (-1708.724) * (-1704.441) (-1724.388) (-1711.132) [-1716.235] -- 0:04:31
600000 -- (-1703.804) [-1698.134] (-1730.666) (-1705.698) * (-1708.541) [-1701.931] (-1711.079) (-1706.305) -- 0:04:31
Average standard deviation of split frequencies: 0.008689
601000 -- [-1702.556] (-1699.310) (-1715.363) (-1708.006) * (-1697.184) (-1707.695) (-1696.596) [-1697.301] -- 0:04:30
602000 -- (-1701.567) (-1706.246) [-1699.959] (-1709.694) * (-1696.034) (-1707.763) [-1698.278] (-1706.826) -- 0:04:29
603000 -- [-1699.655] (-1695.868) (-1708.180) (-1711.301) * [-1707.361] (-1720.773) (-1696.361) (-1697.869) -- 0:04:29
604000 -- (-1704.338) (-1722.886) (-1712.053) [-1694.298] * (-1706.587) (-1705.417) [-1699.289] (-1712.510) -- 0:04:28
605000 -- [-1707.654] (-1702.142) (-1698.125) (-1703.758) * [-1699.104] (-1705.997) (-1703.153) (-1712.761) -- 0:04:27
Average standard deviation of split frequencies: 0.008589
606000 -- [-1695.834] (-1705.313) (-1699.237) (-1725.445) * [-1705.463] (-1700.996) (-1712.327) (-1720.857) -- 0:04:27
607000 -- (-1719.149) (-1695.364) [-1706.387] (-1716.654) * (-1708.933) [-1699.033] (-1704.700) (-1713.723) -- 0:04:26
608000 -- (-1709.486) (-1708.473) [-1707.290] (-1712.028) * (-1703.195) (-1720.043) [-1692.967] (-1724.057) -- 0:04:25
609000 -- (-1700.138) [-1706.809] (-1714.560) (-1711.939) * (-1704.035) [-1712.288] (-1700.404) (-1714.709) -- 0:04:25
610000 -- (-1706.343) (-1695.369) [-1703.340] (-1699.260) * [-1691.932] (-1716.386) (-1699.985) (-1704.388) -- 0:04:24
Average standard deviation of split frequencies: 0.008839
611000 -- [-1703.315] (-1702.414) (-1727.607) (-1696.201) * (-1706.779) (-1722.904) (-1695.026) [-1692.207] -- 0:04:23
612000 -- [-1691.940] (-1719.646) (-1710.249) (-1696.853) * (-1702.293) (-1709.245) [-1695.550] (-1712.141) -- 0:04:23
613000 -- (-1721.390) (-1703.630) (-1709.321) [-1695.580] * (-1705.172) [-1699.157] (-1714.908) (-1707.926) -- 0:04:22
614000 -- (-1702.635) (-1713.302) (-1723.818) [-1698.950] * (-1703.918) (-1694.677) (-1722.007) [-1708.081] -- 0:04:21
615000 -- (-1712.091) [-1698.435] (-1714.187) (-1701.738) * (-1706.601) [-1690.769] (-1710.627) (-1696.343) -- 0:04:21
Average standard deviation of split frequencies: 0.008747
616000 -- (-1701.227) (-1714.713) (-1704.615) [-1698.129] * (-1704.949) (-1703.877) (-1725.484) [-1701.464] -- 0:04:20
617000 -- (-1705.488) [-1703.629] (-1708.731) (-1703.606) * (-1700.601) [-1692.435] (-1707.545) (-1712.803) -- 0:04:19
618000 -- (-1719.724) (-1701.155) (-1691.393) [-1697.992] * (-1709.148) [-1696.169] (-1743.174) (-1701.274) -- 0:04:18
619000 -- (-1720.606) (-1707.487) [-1695.340] (-1700.695) * [-1700.416] (-1706.756) (-1707.037) (-1703.512) -- 0:04:18
620000 -- (-1716.408) [-1707.481] (-1725.674) (-1704.148) * [-1697.604] (-1717.093) (-1711.384) (-1707.310) -- 0:04:17
Average standard deviation of split frequencies: 0.008914
621000 -- (-1711.520) (-1703.319) [-1705.703] (-1706.917) * [-1704.259] (-1717.773) (-1701.031) (-1704.478) -- 0:04:16
622000 -- (-1705.219) (-1711.747) (-1714.880) [-1713.494] * (-1706.382) (-1714.499) [-1700.843] (-1709.838) -- 0:04:16
623000 -- (-1700.212) (-1702.289) (-1718.006) [-1700.729] * (-1709.589) (-1718.031) [-1696.060] (-1709.867) -- 0:04:15
624000 -- (-1711.587) [-1700.796] (-1703.091) (-1709.344) * (-1702.313) (-1707.405) [-1689.188] (-1717.672) -- 0:04:14
625000 -- [-1702.834] (-1715.787) (-1703.696) (-1709.771) * (-1716.703) (-1705.631) [-1689.142] (-1723.290) -- 0:04:14
Average standard deviation of split frequencies: 0.008859
626000 -- (-1715.975) [-1704.895] (-1713.031) (-1708.220) * (-1712.050) [-1701.993] (-1704.643) (-1708.542) -- 0:04:13
627000 -- (-1708.624) (-1704.590) (-1711.669) [-1699.058] * [-1709.556] (-1704.975) (-1721.484) (-1697.729) -- 0:04:12
628000 -- (-1704.788) (-1698.696) [-1694.249] (-1708.590) * [-1701.857] (-1713.414) (-1719.724) (-1702.884) -- 0:04:12
629000 -- (-1707.548) [-1700.115] (-1707.188) (-1711.065) * (-1706.869) [-1703.592] (-1713.935) (-1725.722) -- 0:04:11
630000 -- [-1690.554] (-1704.952) (-1712.604) (-1730.048) * [-1706.219] (-1714.317) (-1711.264) (-1709.715) -- 0:04:10
Average standard deviation of split frequencies: 0.008627
631000 -- (-1695.556) [-1689.808] (-1710.806) (-1709.062) * (-1697.646) (-1724.785) [-1694.247] (-1704.513) -- 0:04:10
632000 -- (-1716.757) (-1696.818) (-1700.410) [-1706.399] * (-1712.459) (-1726.261) [-1705.561] (-1700.864) -- 0:04:09
633000 -- (-1705.478) [-1703.358] (-1712.236) (-1697.362) * (-1699.801) (-1696.616) [-1702.169] (-1703.959) -- 0:04:08
634000 -- (-1721.372) (-1704.214) [-1698.065] (-1705.291) * (-1699.917) (-1716.518) [-1695.797] (-1721.597) -- 0:04:08
635000 -- (-1710.475) (-1722.783) (-1689.271) [-1698.031] * (-1698.950) (-1726.322) [-1697.676] (-1709.245) -- 0:04:07
Average standard deviation of split frequencies: 0.008606
636000 -- (-1714.267) (-1703.248) [-1696.097] (-1690.124) * (-1703.803) (-1718.689) [-1700.270] (-1716.930) -- 0:04:06
637000 -- (-1713.198) (-1708.268) (-1703.741) [-1704.531] * [-1710.216] (-1704.661) (-1699.415) (-1713.379) -- 0:04:06
638000 -- (-1705.746) (-1717.840) [-1696.700] (-1720.157) * [-1696.907] (-1710.167) (-1716.142) (-1708.412) -- 0:04:05
639000 -- (-1710.992) (-1699.871) [-1692.413] (-1714.897) * (-1709.170) [-1696.595] (-1688.728) (-1697.414) -- 0:04:04
640000 -- (-1714.845) (-1713.366) [-1710.359] (-1704.960) * [-1700.112] (-1716.182) (-1692.989) (-1697.173) -- 0:04:04
Average standard deviation of split frequencies: 0.008519
641000 -- (-1714.544) (-1711.238) [-1688.969] (-1690.800) * (-1701.017) [-1705.576] (-1712.604) (-1702.298) -- 0:04:03
642000 -- (-1700.178) (-1712.764) (-1719.565) [-1705.370] * [-1702.763] (-1714.728) (-1721.556) (-1703.101) -- 0:04:02
643000 -- (-1708.926) (-1703.961) [-1694.651] (-1687.515) * [-1696.309] (-1715.191) (-1712.349) (-1720.002) -- 0:04:02
644000 -- (-1718.824) [-1700.693] (-1705.799) (-1691.066) * [-1701.868] (-1720.431) (-1701.534) (-1713.224) -- 0:04:01
645000 -- (-1702.251) [-1693.210] (-1722.903) (-1718.092) * (-1708.439) (-1717.481) (-1694.707) [-1695.758] -- 0:04:00
Average standard deviation of split frequencies: 0.008675
646000 -- [-1700.022] (-1700.802) (-1698.254) (-1709.525) * (-1723.046) (-1732.152) (-1705.011) [-1691.560] -- 0:04:00
647000 -- (-1713.085) (-1708.998) [-1706.405] (-1713.684) * (-1719.749) (-1715.930) (-1703.362) [-1700.240] -- 0:03:59
648000 -- [-1694.190] (-1713.628) (-1714.699) (-1709.739) * [-1693.342] (-1723.898) (-1703.649) (-1703.519) -- 0:03:59
649000 -- [-1694.631] (-1717.446) (-1704.437) (-1715.979) * (-1713.021) [-1722.840] (-1704.261) (-1698.033) -- 0:03:57
650000 -- (-1704.998) (-1719.086) (-1709.501) [-1706.353] * [-1704.831] (-1708.942) (-1706.791) (-1718.415) -- 0:03:57
Average standard deviation of split frequencies: 0.008367
651000 -- [-1694.673] (-1712.453) (-1717.763) (-1697.704) * [-1704.404] (-1700.602) (-1725.835) (-1706.600) -- 0:03:56
652000 -- (-1696.393) [-1691.352] (-1723.411) (-1696.718) * (-1706.255) [-1703.993] (-1726.578) (-1707.188) -- 0:03:55
653000 -- (-1701.566) (-1701.396) (-1704.816) [-1701.241] * (-1712.113) (-1701.382) (-1716.773) [-1711.781] -- 0:03:55
654000 -- (-1730.317) (-1722.313) [-1697.000] (-1704.238) * (-1712.368) (-1696.151) [-1694.736] (-1705.896) -- 0:03:54
655000 -- (-1722.546) [-1699.661] (-1701.358) (-1711.965) * (-1708.835) [-1693.173] (-1713.050) (-1720.689) -- 0:03:53
Average standard deviation of split frequencies: 0.008309
656000 -- (-1715.492) (-1708.269) (-1709.378) [-1700.077] * [-1718.696] (-1712.977) (-1706.563) (-1719.337) -- 0:03:53
657000 -- (-1725.306) [-1705.162] (-1714.355) (-1698.243) * (-1704.690) (-1703.162) [-1700.064] (-1706.484) -- 0:03:52
658000 -- [-1709.590] (-1720.649) (-1702.784) (-1712.981) * (-1699.705) (-1707.492) (-1695.589) [-1707.408] -- 0:03:51
659000 -- (-1711.649) [-1691.204] (-1702.770) (-1708.507) * (-1711.385) (-1709.614) [-1703.806] (-1708.814) -- 0:03:51
660000 -- (-1700.187) (-1692.970) [-1700.476] (-1705.453) * (-1707.165) (-1731.256) (-1719.545) [-1705.520] -- 0:03:50
Average standard deviation of split frequencies: 0.008420
661000 -- (-1706.581) (-1703.708) (-1708.005) [-1700.543] * (-1703.064) (-1719.735) [-1697.342] (-1692.390) -- 0:03:49
662000 -- (-1719.440) [-1704.702] (-1706.458) (-1700.515) * (-1726.030) (-1709.019) (-1708.407) [-1701.987] -- 0:03:49
663000 -- (-1707.966) [-1685.589] (-1702.109) (-1726.869) * (-1720.257) (-1705.902) (-1707.110) [-1706.830] -- 0:03:48
664000 -- [-1706.080] (-1695.424) (-1718.165) (-1714.251) * (-1717.511) [-1695.133] (-1710.994) (-1699.886) -- 0:03:47
665000 -- (-1706.006) (-1711.724) (-1712.052) [-1692.880] * [-1699.999] (-1702.733) (-1711.049) (-1704.916) -- 0:03:47
Average standard deviation of split frequencies: 0.008443
666000 -- (-1710.666) (-1706.234) (-1714.079) [-1698.473] * (-1694.109) [-1694.379] (-1708.483) (-1714.972) -- 0:03:46
667000 -- (-1715.861) [-1692.153] (-1716.717) (-1719.901) * (-1706.088) (-1702.749) (-1713.383) [-1709.082] -- 0:03:45
668000 -- [-1694.982] (-1713.678) (-1709.562) (-1706.844) * (-1693.008) (-1715.338) [-1693.184] (-1717.918) -- 0:03:45
669000 -- (-1703.651) (-1710.681) (-1701.825) [-1702.052] * (-1704.091) [-1699.702] (-1702.387) (-1724.768) -- 0:03:44
670000 -- (-1701.272) [-1700.633] (-1712.870) (-1709.924) * (-1702.523) [-1694.125] (-1702.036) (-1710.466) -- 0:03:43
Average standard deviation of split frequencies: 0.008405
671000 -- [-1695.952] (-1701.149) (-1708.606) (-1701.366) * (-1714.313) (-1703.998) [-1695.447] (-1704.981) -- 0:03:43
672000 -- [-1691.850] (-1705.802) (-1710.426) (-1714.741) * (-1695.889) [-1700.052] (-1706.371) (-1709.871) -- 0:03:42
673000 -- [-1701.871] (-1699.727) (-1723.633) (-1698.130) * (-1706.481) (-1715.232) [-1701.042] (-1719.944) -- 0:03:41
674000 -- (-1725.028) (-1719.122) (-1713.763) [-1689.469] * (-1711.532) [-1700.911] (-1718.257) (-1713.408) -- 0:03:41
675000 -- (-1704.443) (-1698.008) (-1710.490) [-1707.199] * (-1724.456) (-1710.267) (-1701.725) [-1705.010] -- 0:03:40
Average standard deviation of split frequencies: 0.008318
676000 -- (-1706.823) [-1696.496] (-1713.013) (-1693.446) * (-1709.331) (-1708.129) [-1704.435] (-1696.945) -- 0:03:39
677000 -- (-1705.169) [-1692.156] (-1711.721) (-1698.555) * (-1718.873) (-1707.366) [-1705.318] (-1709.836) -- 0:03:38
678000 -- [-1702.601] (-1713.572) (-1713.785) (-1694.776) * (-1709.988) [-1703.303] (-1694.135) (-1727.009) -- 0:03:38
679000 -- [-1710.818] (-1711.563) (-1721.562) (-1712.717) * (-1694.617) [-1711.547] (-1707.752) (-1713.717) -- 0:03:37
680000 -- (-1713.206) (-1695.483) (-1718.644) [-1705.183] * (-1707.362) [-1699.343] (-1712.388) (-1709.409) -- 0:03:36
Average standard deviation of split frequencies: 0.008410
681000 -- [-1704.828] (-1694.864) (-1701.826) (-1718.792) * [-1702.507] (-1694.712) (-1722.837) (-1701.763) -- 0:03:36
682000 -- (-1699.414) (-1689.738) [-1687.770] (-1716.886) * [-1695.957] (-1706.366) (-1704.488) (-1701.175) -- 0:03:35
683000 -- [-1703.874] (-1706.059) (-1698.641) (-1716.577) * [-1690.254] (-1703.824) (-1698.937) (-1712.020) -- 0:03:34
684000 -- (-1701.485) [-1708.957] (-1710.760) (-1722.999) * [-1704.517] (-1702.020) (-1706.054) (-1712.311) -- 0:03:34
685000 -- (-1716.532) (-1711.733) (-1721.975) [-1693.888] * (-1695.142) (-1714.887) [-1714.207] (-1722.090) -- 0:03:33
Average standard deviation of split frequencies: 0.008762
686000 -- [-1693.257] (-1705.021) (-1725.945) (-1704.951) * (-1696.302) (-1707.492) [-1702.568] (-1706.927) -- 0:03:32
687000 -- (-1703.984) [-1701.670] (-1707.869) (-1706.485) * (-1695.881) (-1722.437) [-1704.481] (-1711.167) -- 0:03:32
688000 -- [-1697.929] (-1722.648) (-1700.880) (-1712.742) * (-1707.401) (-1710.524) [-1696.163] (-1701.001) -- 0:03:31
689000 -- (-1712.198) (-1727.001) [-1700.519] (-1701.620) * (-1720.045) [-1692.452] (-1719.757) (-1703.064) -- 0:03:30
690000 -- (-1710.249) (-1699.829) [-1698.073] (-1708.452) * (-1725.649) [-1690.130] (-1709.012) (-1713.365) -- 0:03:30
Average standard deviation of split frequencies: 0.008604
691000 -- (-1695.187) (-1710.825) [-1710.462] (-1701.600) * (-1702.220) [-1707.786] (-1703.817) (-1707.858) -- 0:03:29
692000 -- [-1694.596] (-1704.508) (-1710.073) (-1703.215) * (-1713.415) [-1694.537] (-1703.156) (-1703.228) -- 0:03:28
693000 -- (-1714.185) (-1712.095) [-1698.347] (-1715.544) * (-1702.164) (-1707.826) (-1707.820) [-1694.063] -- 0:03:28
694000 -- (-1705.816) (-1709.839) (-1705.010) [-1693.607] * (-1699.373) [-1706.734] (-1703.044) (-1706.366) -- 0:03:27
695000 -- (-1716.603) (-1697.303) (-1725.696) [-1699.244] * (-1697.211) [-1701.613] (-1730.265) (-1706.641) -- 0:03:26
Average standard deviation of split frequencies: 0.008510
696000 -- (-1703.931) (-1704.684) (-1705.571) [-1702.770] * (-1693.090) [-1693.511] (-1710.329) (-1729.500) -- 0:03:26
697000 -- (-1712.826) (-1718.598) [-1694.404] (-1707.587) * [-1701.411] (-1718.341) (-1704.499) (-1701.409) -- 0:03:25
698000 -- (-1714.875) (-1714.876) [-1699.630] (-1703.387) * (-1717.220) [-1713.904] (-1709.180) (-1704.849) -- 0:03:24
699000 -- (-1708.082) (-1711.846) [-1707.882] (-1705.151) * (-1703.706) [-1701.807] (-1700.238) (-1702.363) -- 0:03:24
700000 -- (-1712.192) (-1715.103) [-1703.763] (-1728.180) * (-1707.804) (-1711.496) [-1696.840] (-1705.793) -- 0:03:23
Average standard deviation of split frequencies: 0.008590
701000 -- [-1701.235] (-1727.664) (-1710.536) (-1726.072) * (-1726.608) (-1710.363) [-1687.349] (-1702.702) -- 0:03:22
702000 -- (-1733.320) (-1715.939) [-1719.194] (-1709.926) * (-1717.121) (-1740.352) [-1709.456] (-1697.708) -- 0:03:22
703000 -- (-1721.025) [-1703.374] (-1703.163) (-1721.470) * (-1711.087) (-1713.880) [-1706.390] (-1688.390) -- 0:03:21
704000 -- [-1707.460] (-1696.020) (-1710.342) (-1714.629) * (-1711.226) (-1707.713) [-1697.440] (-1717.643) -- 0:03:20
705000 -- (-1730.138) [-1702.145] (-1715.485) (-1714.430) * (-1720.812) (-1712.309) (-1695.787) [-1712.005] -- 0:03:20
Average standard deviation of split frequencies: 0.008938
706000 -- [-1708.325] (-1703.178) (-1715.458) (-1708.178) * (-1708.274) [-1705.337] (-1705.864) (-1729.598) -- 0:03:19
707000 -- (-1709.030) (-1697.935) (-1722.374) [-1693.874] * (-1697.757) (-1712.471) [-1695.730] (-1718.185) -- 0:03:18
708000 -- (-1700.396) (-1706.894) [-1700.511] (-1710.072) * (-1707.659) (-1722.264) (-1705.403) [-1691.884] -- 0:03:17
709000 -- (-1701.504) (-1713.398) (-1709.211) [-1700.360] * (-1724.122) (-1701.627) (-1708.878) [-1696.220] -- 0:03:17
710000 -- [-1689.268] (-1709.182) (-1706.653) (-1708.918) * (-1715.721) (-1700.677) [-1700.608] (-1709.119) -- 0:03:16
Average standard deviation of split frequencies: 0.009268
711000 -- [-1697.815] (-1706.861) (-1691.424) (-1704.783) * (-1708.218) (-1707.314) (-1717.534) [-1701.166] -- 0:03:15
712000 -- [-1691.726] (-1710.918) (-1693.886) (-1719.760) * [-1699.334] (-1716.918) (-1717.023) (-1712.742) -- 0:03:15
713000 -- [-1702.486] (-1708.525) (-1704.130) (-1721.110) * (-1705.048) [-1705.444] (-1702.440) (-1717.379) -- 0:03:14
714000 -- (-1707.298) (-1700.482) (-1722.307) [-1710.329] * (-1717.832) [-1714.268] (-1701.817) (-1704.195) -- 0:03:13
715000 -- (-1704.067) (-1710.758) (-1716.585) [-1703.511] * (-1708.220) [-1707.657] (-1708.370) (-1712.139) -- 0:03:13
Average standard deviation of split frequencies: 0.009274
716000 -- [-1697.741] (-1708.469) (-1702.639) (-1718.349) * (-1702.938) (-1727.300) (-1704.018) [-1700.922] -- 0:03:12
717000 -- (-1695.621) [-1698.426] (-1708.737) (-1712.294) * [-1688.955] (-1710.382) (-1710.300) (-1725.490) -- 0:03:11
718000 -- [-1702.005] (-1704.739) (-1717.786) (-1709.381) * [-1706.886] (-1719.957) (-1715.726) (-1708.665) -- 0:03:11
719000 -- (-1698.671) [-1694.913] (-1700.139) (-1709.060) * (-1707.497) (-1706.135) (-1723.274) [-1699.789] -- 0:03:10
720000 -- (-1697.285) (-1699.938) (-1718.703) [-1699.820] * [-1702.517] (-1713.746) (-1706.496) (-1711.642) -- 0:03:09
Average standard deviation of split frequencies: 0.009038
721000 -- (-1697.255) (-1697.942) (-1708.353) [-1702.083] * [-1706.796] (-1719.170) (-1697.226) (-1710.693) -- 0:03:09
722000 -- [-1690.957] (-1699.900) (-1715.406) (-1711.882) * [-1705.468] (-1706.849) (-1701.927) (-1730.083) -- 0:03:08
723000 -- (-1700.269) [-1697.021] (-1705.837) (-1713.723) * (-1711.474) [-1707.464] (-1694.270) (-1718.843) -- 0:03:07
724000 -- [-1692.332] (-1699.511) (-1709.447) (-1715.922) * (-1718.465) [-1699.542] (-1709.814) (-1708.525) -- 0:03:07
725000 -- (-1701.265) [-1703.733] (-1716.804) (-1716.244) * [-1695.190] (-1705.608) (-1694.860) (-1695.988) -- 0:03:06
Average standard deviation of split frequencies: 0.008910
726000 -- (-1717.601) (-1698.801) [-1703.652] (-1710.908) * (-1715.628) [-1707.254] (-1704.607) (-1697.155) -- 0:03:05
727000 -- (-1713.693) (-1722.120) [-1701.717] (-1699.254) * (-1717.529) (-1719.927) [-1695.850] (-1699.891) -- 0:03:05
728000 -- (-1710.745) (-1708.242) (-1715.850) [-1699.000] * [-1697.124] (-1705.444) (-1709.420) (-1703.201) -- 0:03:04
729000 -- (-1707.624) (-1705.331) (-1703.210) [-1695.779] * [-1699.004] (-1703.450) (-1698.073) (-1714.509) -- 0:03:03
730000 -- (-1699.260) [-1692.997] (-1712.757) (-1696.392) * (-1698.260) [-1699.596] (-1696.400) (-1711.924) -- 0:03:03
Average standard deviation of split frequencies: 0.008701
731000 -- (-1704.467) [-1690.222] (-1738.541) (-1707.295) * (-1718.653) (-1702.066) (-1703.142) [-1696.928] -- 0:03:02
732000 -- [-1705.387] (-1693.721) (-1715.688) (-1711.094) * (-1707.511) (-1701.911) (-1700.895) [-1706.864] -- 0:03:01
733000 -- (-1707.178) [-1694.438] (-1706.520) (-1701.214) * (-1706.933) [-1694.668] (-1706.509) (-1717.676) -- 0:03:01
734000 -- (-1709.774) [-1699.839] (-1717.182) (-1718.254) * (-1723.772) (-1711.972) [-1699.540] (-1702.254) -- 0:03:00
735000 -- (-1707.370) (-1701.124) (-1712.908) [-1713.602] * (-1710.365) [-1699.293] (-1719.679) (-1701.686) -- 0:02:59
Average standard deviation of split frequencies: 0.008602
736000 -- (-1706.783) [-1695.093] (-1703.749) (-1718.382) * (-1701.111) (-1707.705) (-1707.526) [-1705.855] -- 0:02:58
737000 -- (-1707.428) [-1705.533] (-1705.281) (-1725.325) * (-1705.439) (-1714.698) [-1698.668] (-1703.010) -- 0:02:58
738000 -- (-1704.060) (-1710.310) [-1709.362] (-1711.003) * (-1723.730) (-1719.082) (-1716.826) [-1690.870] -- 0:02:57
739000 -- [-1706.601] (-1728.040) (-1703.690) (-1713.710) * (-1712.895) (-1714.348) (-1702.512) [-1701.640] -- 0:02:56
740000 -- (-1713.123) (-1707.161) [-1701.139] (-1698.471) * (-1720.982) (-1718.157) [-1704.399] (-1697.618) -- 0:02:56
Average standard deviation of split frequencies: 0.008831
741000 -- (-1715.835) (-1701.024) [-1694.102] (-1695.188) * [-1703.277] (-1715.259) (-1705.744) (-1715.389) -- 0:02:55
742000 -- (-1703.518) (-1716.111) [-1708.362] (-1715.428) * [-1701.866] (-1703.970) (-1701.772) (-1702.753) -- 0:02:54
743000 -- [-1700.062] (-1709.009) (-1732.104) (-1694.453) * (-1713.169) (-1719.879) (-1712.679) [-1703.870] -- 0:02:54
744000 -- [-1700.514] (-1711.945) (-1726.484) (-1701.447) * (-1712.720) [-1702.284] (-1702.178) (-1704.677) -- 0:02:53
745000 -- (-1701.093) (-1717.207) [-1702.519] (-1722.269) * (-1719.696) (-1715.421) (-1711.873) [-1701.299] -- 0:02:52
Average standard deviation of split frequencies: 0.008768
746000 -- (-1705.291) [-1693.356] (-1710.688) (-1708.499) * (-1713.186) (-1692.522) [-1700.299] (-1716.614) -- 0:02:52
747000 -- (-1707.131) [-1713.712] (-1721.972) (-1727.883) * [-1711.090] (-1703.316) (-1727.578) (-1726.196) -- 0:02:51
748000 -- (-1696.293) (-1711.615) [-1709.177] (-1705.621) * [-1695.847] (-1696.855) (-1704.811) (-1720.543) -- 0:02:50
749000 -- [-1698.984] (-1714.663) (-1707.380) (-1703.741) * [-1700.440] (-1697.205) (-1712.015) (-1706.740) -- 0:02:50
750000 -- [-1705.863] (-1699.970) (-1707.677) (-1719.364) * (-1710.324) (-1705.372) [-1700.566] (-1731.636) -- 0:02:49
Average standard deviation of split frequencies: 0.009151
751000 -- (-1701.450) (-1700.373) (-1710.491) [-1704.861] * (-1703.884) (-1707.380) [-1694.929] (-1708.891) -- 0:02:48
752000 -- [-1701.780] (-1704.477) (-1709.507) (-1696.030) * (-1704.486) [-1705.173] (-1697.835) (-1708.503) -- 0:02:48
753000 -- (-1705.398) (-1707.391) (-1706.260) [-1687.321] * [-1700.898] (-1692.498) (-1719.811) (-1709.690) -- 0:02:47
754000 -- (-1712.114) (-1705.193) (-1705.466) [-1695.413] * (-1720.711) [-1696.790] (-1704.185) (-1712.687) -- 0:02:46
755000 -- (-1713.546) (-1721.134) (-1711.214) [-1697.248] * (-1714.511) (-1704.134) (-1719.622) [-1693.638] -- 0:02:46
Average standard deviation of split frequencies: 0.009184
756000 -- (-1705.268) (-1694.011) [-1697.455] (-1701.964) * (-1706.475) (-1705.011) (-1710.021) [-1697.420] -- 0:02:45
757000 -- (-1710.626) [-1691.086] (-1715.097) (-1706.683) * [-1689.680] (-1712.847) (-1720.127) (-1703.459) -- 0:02:44
758000 -- (-1715.867) (-1705.594) (-1706.356) [-1692.127] * (-1711.484) (-1719.082) (-1710.823) [-1711.779] -- 0:02:44
759000 -- [-1700.339] (-1713.376) (-1697.974) (-1701.181) * (-1714.608) (-1703.627) (-1705.459) [-1691.101] -- 0:02:43
760000 -- (-1714.218) [-1689.547] (-1705.796) (-1701.368) * (-1723.373) [-1715.246] (-1706.772) (-1701.915) -- 0:02:42
Average standard deviation of split frequencies: 0.009066
761000 -- (-1721.414) (-1702.708) [-1714.625] (-1700.567) * (-1717.602) (-1696.448) (-1704.867) [-1695.424] -- 0:02:42
762000 -- [-1697.370] (-1703.793) (-1697.541) (-1712.476) * (-1732.370) (-1702.719) [-1707.213] (-1693.518) -- 0:02:41
763000 -- (-1712.561) (-1724.103) [-1698.058] (-1707.694) * [-1696.823] (-1711.628) (-1703.054) (-1703.619) -- 0:02:40
764000 -- (-1722.270) [-1701.597] (-1697.433) (-1708.094) * (-1717.621) (-1703.019) (-1700.388) [-1702.240] -- 0:02:40
765000 -- (-1713.904) (-1710.074) [-1696.301] (-1711.779) * (-1714.635) (-1706.677) [-1695.255] (-1714.821) -- 0:02:39
Average standard deviation of split frequencies: 0.008889
766000 -- [-1697.909] (-1706.645) (-1705.458) (-1711.234) * (-1706.022) (-1711.198) [-1706.062] (-1705.427) -- 0:02:38
767000 -- (-1708.996) (-1706.778) (-1727.842) [-1695.262] * [-1694.495] (-1709.305) (-1709.601) (-1706.698) -- 0:02:37
768000 -- [-1701.604] (-1698.205) (-1713.688) (-1702.984) * (-1703.651) [-1708.841] (-1722.188) (-1715.608) -- 0:02:37
769000 -- (-1697.745) (-1727.790) (-1714.205) [-1709.093] * (-1695.204) (-1715.487) (-1714.835) [-1707.715] -- 0:02:36
770000 -- [-1702.777] (-1705.498) (-1707.558) (-1709.466) * [-1697.553] (-1723.606) (-1706.242) (-1698.974) -- 0:02:35
Average standard deviation of split frequencies: 0.008666
771000 -- (-1698.417) [-1690.236] (-1718.652) (-1716.394) * (-1705.848) (-1710.831) [-1699.425] (-1690.604) -- 0:02:35
772000 -- (-1702.522) (-1697.927) [-1691.037] (-1700.028) * (-1710.183) (-1711.863) [-1713.578] (-1707.285) -- 0:02:34
773000 -- (-1716.722) (-1698.130) (-1707.860) [-1702.037] * (-1697.121) (-1711.762) [-1703.601] (-1711.882) -- 0:02:33
774000 -- (-1715.598) [-1702.397] (-1708.616) (-1703.657) * [-1706.787] (-1706.586) (-1707.627) (-1707.669) -- 0:02:33
775000 -- [-1698.413] (-1695.581) (-1708.835) (-1703.025) * [-1700.756] (-1702.213) (-1712.958) (-1694.594) -- 0:02:32
Average standard deviation of split frequencies: 0.008869
776000 -- (-1710.483) (-1734.117) [-1689.022] (-1691.194) * (-1705.668) (-1711.534) (-1718.847) [-1694.525] -- 0:02:31
777000 -- (-1720.749) (-1721.360) [-1707.712] (-1704.862) * (-1709.351) (-1696.029) (-1707.178) [-1692.944] -- 0:02:31
778000 -- (-1701.589) (-1702.732) (-1707.644) [-1700.457] * (-1710.925) (-1699.433) (-1715.584) [-1701.579] -- 0:02:30
779000 -- (-1704.094) (-1713.892) [-1718.010] (-1702.306) * (-1712.606) (-1712.288) [-1698.796] (-1706.483) -- 0:02:29
780000 -- (-1718.684) (-1704.751) (-1715.521) [-1693.522] * (-1715.058) [-1684.224] (-1703.301) (-1702.801) -- 0:02:29
Average standard deviation of split frequencies: 0.008811
781000 -- (-1694.157) [-1708.803] (-1708.319) (-1699.038) * (-1692.564) [-1695.688] (-1711.543) (-1705.872) -- 0:02:28
782000 -- (-1697.932) [-1699.068] (-1701.193) (-1702.406) * (-1698.997) (-1724.371) (-1718.205) [-1700.382] -- 0:02:28
783000 -- (-1703.640) (-1712.440) [-1693.055] (-1710.106) * (-1711.331) [-1693.356] (-1706.664) (-1704.183) -- 0:02:27
784000 -- (-1706.932) (-1713.785) [-1716.254] (-1710.304) * (-1706.104) [-1697.554] (-1703.922) (-1712.097) -- 0:02:26
785000 -- (-1705.690) [-1706.283] (-1708.059) (-1709.695) * [-1699.778] (-1699.958) (-1708.466) (-1703.147) -- 0:02:25
Average standard deviation of split frequencies: 0.008760
786000 -- (-1712.526) [-1695.562] (-1716.612) (-1712.467) * (-1712.303) (-1702.228) [-1696.689] (-1701.708) -- 0:02:25
787000 -- (-1714.829) [-1694.355] (-1696.354) (-1696.725) * (-1698.115) (-1729.352) (-1706.701) [-1706.236] -- 0:02:24
788000 -- (-1713.646) [-1708.249] (-1719.908) (-1695.070) * (-1714.050) [-1706.365] (-1706.901) (-1701.128) -- 0:02:23
789000 -- [-1699.572] (-1712.170) (-1702.776) (-1718.826) * (-1704.314) (-1707.785) (-1705.794) [-1693.589] -- 0:02:23
790000 -- (-1707.618) (-1703.209) (-1716.326) [-1698.751] * (-1701.018) (-1707.035) (-1716.410) [-1698.735] -- 0:02:22
Average standard deviation of split frequencies: 0.008700
791000 -- (-1703.310) (-1718.852) (-1732.554) [-1702.767] * (-1704.817) [-1701.604] (-1724.871) (-1722.607) -- 0:02:21
792000 -- (-1711.529) (-1714.285) (-1717.144) [-1704.336] * (-1713.566) [-1695.772] (-1704.912) (-1707.830) -- 0:02:21
793000 -- [-1695.001] (-1718.772) (-1714.769) (-1714.767) * [-1709.142] (-1709.020) (-1710.298) (-1717.440) -- 0:02:20
794000 -- (-1697.350) [-1708.816] (-1698.468) (-1716.378) * (-1715.894) [-1695.427] (-1711.040) (-1719.400) -- 0:02:19
795000 -- (-1717.879) (-1701.503) [-1698.461] (-1714.575) * (-1707.356) [-1693.699] (-1713.418) (-1711.898) -- 0:02:18
Average standard deviation of split frequencies: 0.008850
796000 -- [-1708.326] (-1696.354) (-1706.236) (-1718.029) * (-1700.678) (-1718.538) [-1690.824] (-1703.542) -- 0:02:18
797000 -- (-1710.196) (-1709.980) (-1700.498) [-1702.635] * (-1708.944) (-1703.102) [-1705.442] (-1721.203) -- 0:02:17
798000 -- [-1710.276] (-1697.062) (-1697.297) (-1707.151) * (-1721.660) (-1699.879) [-1701.161] (-1719.046) -- 0:02:16
799000 -- (-1723.433) [-1696.204] (-1711.713) (-1707.311) * (-1711.204) (-1721.516) [-1698.744] (-1700.192) -- 0:02:16
800000 -- (-1700.750) (-1701.907) (-1716.053) [-1706.735] * (-1708.064) (-1737.191) (-1705.966) [-1702.861] -- 0:02:15
Average standard deviation of split frequencies: 0.008791
801000 -- [-1699.756] (-1713.326) (-1706.292) (-1722.458) * [-1703.409] (-1729.274) (-1706.395) (-1716.862) -- 0:02:14
802000 -- [-1706.639] (-1702.483) (-1709.587) (-1701.790) * (-1706.207) (-1716.627) [-1709.006] (-1714.162) -- 0:02:14
803000 -- [-1697.362] (-1697.558) (-1701.704) (-1714.430) * (-1721.840) (-1717.367) [-1701.729] (-1699.719) -- 0:02:13
804000 -- (-1713.162) (-1708.844) [-1699.741] (-1718.274) * (-1709.730) (-1714.220) (-1709.323) [-1693.636] -- 0:02:12
805000 -- (-1720.972) [-1699.649] (-1699.950) (-1689.495) * (-1706.254) [-1714.973] (-1712.569) (-1722.703) -- 0:02:12
Average standard deviation of split frequencies: 0.008684
806000 -- (-1706.932) (-1708.724) (-1706.867) [-1690.770] * (-1708.407) (-1707.161) [-1705.731] (-1736.005) -- 0:02:11
807000 -- [-1700.987] (-1711.562) (-1724.087) (-1703.027) * [-1704.416] (-1720.947) (-1704.412) (-1725.048) -- 0:02:10
808000 -- [-1691.138] (-1714.829) (-1702.345) (-1700.851) * (-1706.873) (-1728.956) (-1724.697) [-1704.238] -- 0:02:10
809000 -- (-1695.347) (-1709.091) [-1693.993] (-1704.866) * [-1702.713] (-1722.095) (-1723.681) (-1699.865) -- 0:02:09
810000 -- (-1702.219) [-1691.813] (-1709.325) (-1724.025) * (-1698.826) (-1704.810) (-1697.662) [-1702.405] -- 0:02:08
Average standard deviation of split frequencies: 0.008472
811000 -- (-1699.781) (-1702.950) [-1709.863] (-1717.296) * [-1697.846] (-1697.475) (-1714.299) (-1701.829) -- 0:02:08
812000 -- (-1708.743) (-1715.497) (-1709.570) [-1692.013] * (-1697.234) (-1708.316) [-1701.466] (-1704.722) -- 0:02:07
813000 -- (-1714.758) (-1704.213) (-1697.129) [-1713.469] * (-1713.271) [-1697.278] (-1711.933) (-1704.252) -- 0:02:06
814000 -- (-1710.137) (-1717.801) (-1690.867) [-1699.164] * [-1698.372] (-1686.967) (-1724.594) (-1698.771) -- 0:02:06
815000 -- [-1702.765] (-1705.206) (-1715.268) (-1717.690) * (-1695.479) [-1683.021] (-1708.891) (-1705.660) -- 0:02:05
Average standard deviation of split frequencies: 0.008377
816000 -- (-1708.836) (-1700.963) (-1718.895) [-1692.832] * (-1708.170) [-1703.519] (-1705.898) (-1717.877) -- 0:02:04
817000 -- [-1697.564] (-1708.539) (-1709.854) (-1701.784) * (-1709.375) [-1689.055] (-1711.007) (-1714.276) -- 0:02:04
818000 -- [-1704.947] (-1697.203) (-1710.475) (-1706.924) * (-1703.375) (-1697.480) (-1714.575) [-1700.423] -- 0:02:03
819000 -- [-1700.070] (-1705.089) (-1713.368) (-1708.281) * (-1708.984) [-1689.395] (-1701.509) (-1708.369) -- 0:02:02
820000 -- [-1698.490] (-1708.885) (-1709.216) (-1720.721) * [-1695.397] (-1711.521) (-1691.656) (-1710.089) -- 0:02:02
Average standard deviation of split frequencies: 0.008457
821000 -- [-1698.956] (-1694.588) (-1711.248) (-1715.708) * [-1697.663] (-1720.716) (-1695.825) (-1712.113) -- 0:02:01
822000 -- [-1693.136] (-1703.318) (-1706.783) (-1702.090) * (-1716.848) (-1698.345) (-1709.446) [-1702.606] -- 0:02:00
823000 -- [-1698.546] (-1702.469) (-1710.722) (-1710.817) * (-1716.237) (-1702.097) [-1703.791] (-1715.760) -- 0:02:00
824000 -- (-1700.020) [-1703.159] (-1709.855) (-1699.122) * [-1711.108] (-1721.545) (-1725.938) (-1707.793) -- 0:01:59
825000 -- (-1708.542) (-1704.960) (-1713.749) [-1688.878] * [-1689.940] (-1696.767) (-1710.256) (-1708.901) -- 0:01:58
Average standard deviation of split frequencies: 0.008473
826000 -- (-1709.334) (-1709.412) (-1713.125) [-1698.844] * (-1693.501) (-1704.547) [-1712.332] (-1719.319) -- 0:01:57
827000 -- [-1685.710] (-1717.063) (-1709.263) (-1707.028) * (-1693.470) (-1694.360) (-1723.327) [-1716.695] -- 0:01:57
828000 -- (-1708.910) (-1716.139) (-1713.913) [-1701.532] * [-1715.248] (-1716.115) (-1716.118) (-1705.420) -- 0:01:56
829000 -- [-1706.447] (-1704.346) (-1719.543) (-1703.617) * (-1708.334) (-1702.193) (-1711.354) [-1700.235] -- 0:01:55
830000 -- (-1707.123) (-1695.645) (-1703.710) [-1692.371] * [-1702.719] (-1697.943) (-1718.915) (-1708.392) -- 0:01:55
Average standard deviation of split frequencies: 0.008489
831000 -- (-1718.788) (-1707.206) (-1704.154) [-1695.341] * (-1703.662) (-1712.627) [-1699.791] (-1711.524) -- 0:01:54
832000 -- (-1699.839) (-1730.735) [-1697.051] (-1719.463) * [-1704.004] (-1704.762) (-1706.413) (-1700.639) -- 0:01:53
833000 -- (-1717.045) (-1714.937) [-1707.489] (-1721.214) * [-1704.571] (-1707.196) (-1708.959) (-1703.482) -- 0:01:53
834000 -- (-1718.588) [-1697.583] (-1708.755) (-1707.996) * [-1695.165] (-1707.448) (-1708.326) (-1704.132) -- 0:01:52
835000 -- [-1704.509] (-1707.231) (-1706.391) (-1702.452) * (-1703.463) (-1704.543) (-1703.236) [-1704.010] -- 0:01:51
Average standard deviation of split frequencies: 0.008427
836000 -- [-1702.981] (-1701.767) (-1712.164) (-1717.809) * (-1701.111) (-1714.969) [-1714.264] (-1706.114) -- 0:01:51
837000 -- (-1705.808) (-1702.910) (-1703.559) [-1697.794] * (-1704.971) (-1699.701) (-1704.921) [-1707.256] -- 0:01:50
838000 -- (-1701.788) (-1704.930) (-1716.720) [-1702.321] * (-1716.602) (-1704.432) [-1702.630] (-1706.444) -- 0:01:49
839000 -- (-1723.402) (-1697.440) [-1697.427] (-1696.662) * (-1713.926) (-1703.258) [-1706.138] (-1714.245) -- 0:01:49
840000 -- (-1716.540) [-1695.092] (-1710.720) (-1701.210) * [-1698.082] (-1704.062) (-1693.155) (-1727.629) -- 0:01:48
Average standard deviation of split frequencies: 0.008341
841000 -- (-1716.940) [-1693.940] (-1721.043) (-1708.288) * (-1708.120) (-1692.761) [-1691.062] (-1714.438) -- 0:01:47
842000 -- (-1708.147) (-1702.423) [-1700.707] (-1714.344) * (-1705.986) [-1691.886] (-1711.223) (-1716.978) -- 0:01:47
843000 -- [-1711.807] (-1713.882) (-1708.340) (-1695.658) * [-1705.226] (-1710.993) (-1702.299) (-1711.052) -- 0:01:46
844000 -- (-1718.172) (-1722.373) [-1691.856] (-1704.270) * [-1695.828] (-1705.714) (-1714.759) (-1711.995) -- 0:01:45
845000 -- [-1709.166] (-1711.236) (-1704.799) (-1719.970) * [-1690.628] (-1704.515) (-1718.068) (-1704.462) -- 0:01:45
Average standard deviation of split frequencies: 0.008175
846000 -- [-1697.693] (-1719.741) (-1705.059) (-1713.339) * (-1702.038) (-1707.554) (-1694.449) [-1696.007] -- 0:01:44
847000 -- (-1710.840) (-1711.364) [-1688.718] (-1697.733) * (-1712.066) [-1700.383] (-1715.417) (-1699.483) -- 0:01:43
848000 -- (-1703.175) [-1703.761] (-1708.629) (-1707.701) * [-1697.518] (-1713.104) (-1722.103) (-1699.855) -- 0:01:43
849000 -- (-1708.499) (-1706.061) [-1698.139] (-1703.765) * [-1698.887] (-1706.904) (-1707.624) (-1702.237) -- 0:01:42
850000 -- (-1700.002) (-1710.892) (-1716.394) [-1703.670] * [-1698.626] (-1716.524) (-1704.201) (-1704.123) -- 0:01:41
Average standard deviation of split frequencies: 0.008252
851000 -- (-1710.308) [-1710.350] (-1705.848) (-1705.595) * (-1712.105) (-1710.208) [-1709.787] (-1724.354) -- 0:01:41
852000 -- (-1720.908) (-1709.022) (-1710.041) [-1695.846] * (-1707.249) [-1708.193] (-1724.669) (-1716.442) -- 0:01:40
853000 -- (-1705.426) (-1708.357) [-1698.629] (-1699.305) * (-1715.990) (-1702.889) (-1712.880) [-1695.285] -- 0:01:39
854000 -- [-1698.027] (-1720.682) (-1709.487) (-1694.498) * [-1703.249] (-1706.167) (-1712.148) (-1699.206) -- 0:01:38
855000 -- [-1702.040] (-1704.147) (-1696.579) (-1703.515) * [-1700.380] (-1714.443) (-1726.859) (-1702.631) -- 0:01:38
Average standard deviation of split frequencies: 0.008117
856000 -- (-1713.330) (-1715.239) (-1724.884) [-1715.845] * [-1709.070] (-1705.413) (-1719.065) (-1700.325) -- 0:01:37
857000 -- (-1711.038) [-1694.379] (-1712.081) (-1702.975) * (-1707.223) (-1701.168) [-1690.935] (-1719.204) -- 0:01:36
858000 -- (-1711.262) [-1700.222] (-1701.775) (-1711.673) * (-1704.756) (-1701.743) (-1697.627) [-1720.505] -- 0:01:36
859000 -- (-1713.599) (-1711.141) (-1721.822) [-1705.114] * (-1708.809) (-1700.251) [-1693.453] (-1707.903) -- 0:01:35
860000 -- (-1699.238) (-1709.201) (-1725.776) [-1695.417] * [-1695.125] (-1711.964) (-1705.631) (-1712.281) -- 0:01:34
Average standard deviation of split frequencies: 0.008253
861000 -- (-1698.248) (-1709.598) (-1722.161) [-1688.404] * [-1699.474] (-1714.423) (-1712.027) (-1699.722) -- 0:01:34
862000 -- [-1695.501] (-1706.685) (-1721.808) (-1691.351) * [-1709.524] (-1711.282) (-1709.638) (-1701.711) -- 0:01:33
863000 -- (-1702.734) (-1709.181) (-1720.595) [-1704.262] * (-1705.548) (-1721.293) [-1697.885] (-1709.977) -- 0:01:33
864000 -- [-1698.721] (-1691.031) (-1710.405) (-1704.258) * (-1702.849) (-1704.141) [-1702.003] (-1713.133) -- 0:01:32
865000 -- (-1718.703) (-1699.708) (-1715.438) [-1700.676] * [-1709.429] (-1730.474) (-1702.013) (-1702.901) -- 0:01:31
Average standard deviation of split frequencies: 0.008364
866000 -- (-1701.968) (-1701.101) (-1711.786) [-1703.346] * (-1717.704) (-1712.452) (-1695.472) [-1716.102] -- 0:01:30
867000 -- (-1714.234) [-1701.104] (-1706.411) (-1705.659) * (-1741.084) (-1724.373) (-1696.977) [-1701.159] -- 0:01:30
868000 -- (-1706.441) [-1690.155] (-1709.988) (-1728.099) * (-1734.575) [-1700.108] (-1708.180) (-1712.399) -- 0:01:29
869000 -- (-1713.856) [-1703.505] (-1705.332) (-1728.184) * (-1714.357) [-1701.877] (-1711.743) (-1701.526) -- 0:01:28
870000 -- (-1708.824) [-1688.723] (-1712.726) (-1721.877) * [-1702.875] (-1709.185) (-1706.521) (-1706.534) -- 0:01:28
Average standard deviation of split frequencies: 0.008359
871000 -- (-1704.188) [-1698.191] (-1692.684) (-1722.912) * [-1694.152] (-1704.944) (-1712.320) (-1699.169) -- 0:01:27
872000 -- [-1711.388] (-1721.000) (-1703.976) (-1710.346) * (-1699.150) (-1710.109) (-1710.227) [-1695.478] -- 0:01:26
873000 -- (-1706.948) (-1702.417) [-1702.538] (-1710.320) * (-1710.550) [-1692.727] (-1717.304) (-1701.229) -- 0:01:26
874000 -- (-1716.408) (-1713.327) (-1707.058) [-1688.821] * (-1692.348) (-1705.003) (-1700.812) [-1703.682] -- 0:01:25
875000 -- (-1729.378) (-1703.618) (-1708.241) [-1697.488] * [-1696.687] (-1710.825) (-1699.947) (-1722.013) -- 0:01:24
Average standard deviation of split frequencies: 0.008290
876000 -- (-1718.732) [-1708.086] (-1694.262) (-1702.177) * (-1709.228) [-1697.709] (-1717.936) (-1710.614) -- 0:01:24
877000 -- (-1716.107) (-1701.146) [-1703.976] (-1699.378) * (-1710.298) (-1706.762) (-1711.129) [-1702.355] -- 0:01:23
878000 -- (-1710.229) (-1702.590) [-1708.358] (-1710.654) * (-1713.038) [-1698.618] (-1704.288) (-1708.239) -- 0:01:22
879000 -- [-1699.407] (-1711.572) (-1721.426) (-1696.765) * (-1714.873) [-1695.700] (-1705.529) (-1725.209) -- 0:01:22
880000 -- [-1700.644] (-1709.576) (-1717.658) (-1698.621) * [-1690.488] (-1695.972) (-1710.027) (-1706.466) -- 0:01:21
Average standard deviation of split frequencies: 0.008037
881000 -- [-1699.006] (-1716.791) (-1710.963) (-1708.683) * (-1699.327) (-1710.018) [-1700.036] (-1714.214) -- 0:01:20
882000 -- (-1697.860) (-1724.530) [-1695.149] (-1711.405) * [-1703.928] (-1705.113) (-1713.609) (-1697.236) -- 0:01:20
883000 -- (-1706.145) (-1717.735) [-1706.106] (-1713.112) * (-1718.161) (-1704.546) (-1711.429) [-1708.859] -- 0:01:19
884000 -- (-1702.968) (-1705.645) [-1698.993] (-1707.864) * [-1690.571] (-1710.026) (-1712.621) (-1717.604) -- 0:01:18
885000 -- (-1703.314) [-1703.255] (-1712.203) (-1699.857) * [-1708.353] (-1719.809) (-1710.094) (-1707.554) -- 0:01:18
Average standard deviation of split frequencies: 0.008119
886000 -- (-1713.939) (-1711.196) [-1695.474] (-1703.153) * (-1712.629) (-1735.944) (-1710.202) [-1715.079] -- 0:01:17
887000 -- [-1697.403] (-1706.531) (-1698.361) (-1700.042) * [-1702.383] (-1700.552) (-1718.648) (-1703.193) -- 0:01:16
888000 -- (-1697.282) (-1703.805) (-1704.943) [-1702.031] * (-1692.490) [-1712.638] (-1712.945) (-1696.838) -- 0:01:16
889000 -- [-1713.739] (-1703.315) (-1719.336) (-1709.109) * [-1693.711] (-1714.595) (-1704.474) (-1705.226) -- 0:01:15
890000 -- (-1698.855) (-1696.457) [-1698.964] (-1707.980) * (-1702.669) (-1716.552) (-1708.573) [-1696.004] -- 0:01:14
Average standard deviation of split frequencies: 0.008106
891000 -- (-1705.736) (-1707.597) (-1709.692) [-1700.872] * (-1715.557) [-1711.320] (-1704.526) (-1702.811) -- 0:01:14
892000 -- [-1694.815] (-1713.333) (-1713.290) (-1710.948) * (-1709.346) [-1704.019] (-1725.853) (-1700.769) -- 0:01:13
893000 -- [-1695.240] (-1707.995) (-1714.211) (-1717.404) * (-1714.563) (-1714.019) (-1702.712) [-1696.048] -- 0:01:12
894000 -- (-1699.565) (-1724.060) (-1717.904) [-1697.977] * (-1714.713) (-1710.028) (-1700.984) [-1701.069] -- 0:01:11
895000 -- (-1710.879) (-1702.196) (-1728.019) [-1689.800] * (-1704.465) (-1728.783) (-1706.128) [-1705.612] -- 0:01:11
Average standard deviation of split frequencies: 0.008130
896000 -- (-1695.183) [-1703.570] (-1710.336) (-1715.146) * [-1697.508] (-1710.894) (-1710.965) (-1691.994) -- 0:01:10
897000 -- (-1706.478) (-1706.513) (-1702.501) [-1708.015] * (-1727.065) [-1711.260] (-1724.705) (-1699.567) -- 0:01:09
898000 -- [-1699.422] (-1719.368) (-1725.749) (-1695.794) * [-1704.305] (-1707.524) (-1704.252) (-1700.964) -- 0:01:09
899000 -- (-1709.440) (-1713.887) (-1693.481) [-1696.588] * [-1698.188] (-1714.681) (-1710.784) (-1705.144) -- 0:01:08
900000 -- [-1699.955] (-1718.971) (-1706.458) (-1697.791) * (-1699.653) (-1718.924) (-1705.593) [-1706.187] -- 0:01:07
Average standard deviation of split frequencies: 0.008095
901000 -- (-1696.320) [-1710.328] (-1712.223) (-1705.407) * (-1707.012) [-1701.528] (-1710.149) (-1704.592) -- 0:01:07
902000 -- (-1705.582) [-1691.064] (-1705.395) (-1704.842) * (-1703.455) (-1711.766) [-1699.047] (-1697.679) -- 0:01:06
903000 -- (-1712.353) (-1697.671) [-1692.356] (-1707.706) * [-1703.788] (-1724.328) (-1693.486) (-1697.516) -- 0:01:05
904000 -- (-1725.102) [-1710.959] (-1703.134) (-1703.242) * (-1696.054) (-1711.432) [-1700.066] (-1695.426) -- 0:01:05
905000 -- [-1707.487] (-1708.510) (-1705.286) (-1723.526) * (-1701.104) (-1716.172) [-1697.448] (-1706.219) -- 0:01:04
Average standard deviation of split frequencies: 0.008111
906000 -- (-1704.718) [-1700.449] (-1704.899) (-1710.020) * (-1703.677) (-1708.535) (-1694.739) [-1699.046] -- 0:01:03
907000 -- (-1693.135) [-1699.523] (-1707.491) (-1698.792) * (-1704.371) (-1719.443) (-1703.684) [-1695.086] -- 0:01:03
908000 -- (-1712.803) (-1693.909) (-1704.718) [-1712.563] * (-1718.625) (-1714.754) (-1704.883) [-1697.612] -- 0:01:02
909000 -- [-1703.271] (-1697.222) (-1711.579) (-1724.497) * (-1723.211) (-1707.569) [-1708.058] (-1711.520) -- 0:01:01
910000 -- [-1707.683] (-1717.283) (-1698.158) (-1718.942) * (-1714.259) (-1708.571) [-1695.067] (-1697.076) -- 0:01:01
Average standard deviation of split frequencies: 0.008169
911000 -- [-1703.583] (-1711.783) (-1709.812) (-1705.026) * (-1687.627) (-1707.900) (-1718.540) [-1700.051] -- 0:01:00
912000 -- (-1701.287) (-1697.348) [-1705.606] (-1725.318) * (-1694.078) (-1716.160) (-1702.900) [-1693.746] -- 0:00:59
913000 -- (-1703.785) (-1698.834) [-1697.865] (-1741.908) * [-1702.343] (-1700.795) (-1718.071) (-1723.441) -- 0:00:59
914000 -- (-1714.339) [-1704.164] (-1711.158) (-1710.061) * (-1712.204) [-1701.913] (-1709.688) (-1699.483) -- 0:00:58
915000 -- (-1698.560) (-1722.016) (-1709.074) [-1702.905] * [-1701.897] (-1719.402) (-1707.650) (-1695.042) -- 0:00:57
Average standard deviation of split frequencies: 0.008305
916000 -- [-1695.126] (-1700.882) (-1707.532) (-1705.991) * (-1732.209) (-1703.913) (-1724.573) [-1694.873] -- 0:00:57
917000 -- [-1696.694] (-1715.853) (-1727.261) (-1695.559) * (-1725.384) (-1698.477) [-1706.918] (-1707.925) -- 0:00:56
918000 -- (-1708.814) (-1700.486) (-1725.576) [-1695.273] * (-1717.737) (-1702.007) (-1700.070) [-1703.950] -- 0:00:55
919000 -- (-1706.805) [-1698.053] (-1714.695) (-1711.652) * [-1701.553] (-1704.993) (-1713.341) (-1694.969) -- 0:00:54
920000 -- (-1719.829) (-1711.672) [-1688.292] (-1714.694) * [-1689.954] (-1719.850) (-1714.125) (-1717.907) -- 0:00:54
Average standard deviation of split frequencies: 0.008270
921000 -- (-1705.263) [-1706.328] (-1702.673) (-1714.910) * (-1697.052) (-1715.941) [-1699.595] (-1703.749) -- 0:00:53
922000 -- (-1693.392) (-1713.316) (-1699.929) [-1688.907] * (-1707.152) (-1705.485) [-1695.055] (-1707.424) -- 0:00:52
923000 -- (-1703.118) (-1702.726) [-1701.160] (-1698.985) * (-1721.682) (-1719.901) [-1705.460] (-1700.994) -- 0:00:52
924000 -- (-1710.899) (-1710.586) (-1707.418) [-1705.404] * (-1721.087) (-1701.030) (-1707.688) [-1697.408] -- 0:00:51
925000 -- (-1713.046) (-1722.880) [-1703.718] (-1716.507) * (-1709.262) (-1703.481) [-1700.106] (-1688.957) -- 0:00:50
Average standard deviation of split frequencies: 0.008257
926000 -- [-1693.225] (-1705.022) (-1705.467) (-1717.080) * (-1720.161) (-1698.616) (-1703.133) [-1698.405] -- 0:00:50
927000 -- [-1702.929] (-1715.104) (-1702.913) (-1719.594) * (-1714.120) (-1698.726) (-1716.011) [-1701.407] -- 0:00:49
928000 -- (-1709.567) [-1700.720] (-1710.859) (-1707.046) * [-1699.491] (-1704.789) (-1714.515) (-1732.029) -- 0:00:48
929000 -- (-1713.343) (-1706.857) [-1695.781] (-1721.399) * (-1699.394) (-1714.482) [-1709.830] (-1712.266) -- 0:00:48
930000 -- (-1708.552) (-1699.312) [-1689.217] (-1704.577) * (-1712.505) (-1700.969) [-1706.378] (-1705.071) -- 0:00:47
Average standard deviation of split frequencies: 0.008262
931000 -- (-1710.991) (-1722.366) (-1701.698) [-1698.604] * [-1700.808] (-1710.985) (-1697.640) (-1705.349) -- 0:00:46
932000 -- (-1714.001) (-1714.744) [-1692.201] (-1713.182) * (-1732.110) (-1707.573) [-1699.292] (-1701.206) -- 0:00:46
933000 -- (-1713.557) [-1709.051] (-1700.822) (-1716.744) * (-1715.131) (-1703.944) (-1722.300) [-1697.325] -- 0:00:45
934000 -- (-1709.457) (-1706.453) (-1701.375) [-1692.692] * (-1704.968) (-1709.738) (-1739.276) [-1703.953] -- 0:00:44
935000 -- (-1708.213) (-1698.451) [-1703.099] (-1705.567) * (-1711.189) (-1708.206) (-1726.666) [-1707.418] -- 0:00:44
Average standard deviation of split frequencies: 0.008283
936000 -- (-1698.418) (-1711.185) [-1708.546] (-1702.807) * [-1690.693] (-1696.973) (-1711.412) (-1709.395) -- 0:00:43
937000 -- (-1713.014) (-1695.075) [-1701.268] (-1705.061) * (-1703.542) (-1699.178) (-1701.576) [-1708.346] -- 0:00:42
938000 -- (-1717.514) (-1692.004) (-1705.952) [-1697.978] * (-1725.505) (-1706.531) [-1710.258] (-1715.968) -- 0:00:42
939000 -- (-1723.243) [-1698.183] (-1709.664) (-1705.970) * [-1712.164] (-1689.345) (-1715.779) (-1717.730) -- 0:00:41
940000 -- (-1716.734) (-1691.240) [-1695.405] (-1704.586) * (-1713.529) [-1698.265] (-1735.549) (-1713.914) -- 0:00:40
Average standard deviation of split frequencies: 0.008120
941000 -- (-1710.151) (-1705.467) (-1709.989) [-1700.638] * (-1719.582) [-1712.487] (-1692.971) (-1711.067) -- 0:00:40
942000 -- (-1707.864) (-1711.582) (-1708.397) [-1699.455] * (-1700.018) (-1713.515) [-1698.899] (-1711.386) -- 0:00:39
943000 -- (-1717.388) [-1703.616] (-1714.423) (-1705.074) * (-1707.142) (-1718.533) [-1697.843] (-1700.436) -- 0:00:38
944000 -- [-1696.973] (-1702.170) (-1717.527) (-1714.848) * (-1704.481) (-1716.763) [-1708.240] (-1714.697) -- 0:00:37
945000 -- (-1716.082) [-1702.339] (-1721.277) (-1707.389) * (-1703.754) (-1699.697) [-1707.007] (-1702.170) -- 0:00:37
Average standard deviation of split frequencies: 0.008074
946000 -- (-1704.596) (-1713.464) [-1707.389] (-1696.753) * [-1692.571] (-1696.707) (-1706.740) (-1700.869) -- 0:00:36
947000 -- (-1712.477) [-1698.891] (-1703.069) (-1703.620) * (-1700.115) (-1717.385) [-1697.650] (-1710.466) -- 0:00:35
948000 -- (-1719.796) [-1702.150] (-1699.733) (-1711.427) * [-1699.994] (-1714.268) (-1697.541) (-1695.306) -- 0:00:35
949000 -- (-1698.847) [-1701.614] (-1713.780) (-1714.227) * (-1703.202) (-1709.950) (-1712.786) [-1703.764] -- 0:00:34
950000 -- (-1698.686) (-1709.044) (-1704.882) [-1697.220] * (-1715.103) [-1710.764] (-1713.091) (-1694.653) -- 0:00:33
Average standard deviation of split frequencies: 0.008075
951000 -- (-1698.793) [-1702.364] (-1715.038) (-1712.559) * (-1697.856) (-1710.624) (-1715.803) [-1701.962] -- 0:00:33
952000 -- [-1706.350] (-1708.194) (-1706.111) (-1701.275) * [-1695.647] (-1701.494) (-1715.857) (-1707.167) -- 0:00:32
953000 -- (-1709.156) (-1695.093) [-1695.174] (-1709.157) * (-1708.827) (-1716.376) (-1712.112) [-1702.775] -- 0:00:31
954000 -- (-1724.128) [-1690.454] (-1699.001) (-1697.329) * (-1712.385) (-1717.937) (-1709.840) [-1698.081] -- 0:00:31
955000 -- [-1701.076] (-1716.205) (-1708.585) (-1710.743) * (-1694.498) (-1716.909) [-1700.997] (-1703.798) -- 0:00:30
Average standard deviation of split frequencies: 0.008016
956000 -- (-1716.430) (-1697.010) [-1701.871] (-1713.333) * [-1700.038] (-1709.845) (-1709.287) (-1723.021) -- 0:00:29
957000 -- (-1704.639) (-1702.585) [-1697.708] (-1700.641) * (-1712.217) (-1714.177) [-1685.571] (-1709.068) -- 0:00:29
958000 -- (-1710.086) [-1698.521] (-1709.501) (-1711.385) * (-1707.817) (-1703.942) (-1713.584) [-1711.457] -- 0:00:28
959000 -- (-1705.127) (-1699.148) [-1700.791] (-1713.803) * (-1705.696) (-1714.473) [-1700.797] (-1701.583) -- 0:00:27
960000 -- [-1694.703] (-1697.209) (-1711.004) (-1719.209) * [-1696.537] (-1707.774) (-1696.558) (-1708.963) -- 0:00:27
Average standard deviation of split frequencies: 0.007812
961000 -- (-1713.250) (-1692.867) (-1700.076) [-1708.184] * [-1695.057] (-1709.095) (-1703.773) (-1720.080) -- 0:00:26
962000 -- (-1697.776) [-1694.144] (-1716.670) (-1715.298) * (-1708.722) (-1693.369) (-1699.411) [-1694.933] -- 0:00:25
963000 -- (-1696.242) (-1702.170) [-1697.402] (-1696.926) * (-1706.702) (-1715.678) (-1715.588) [-1698.254] -- 0:00:25
964000 -- (-1710.869) (-1708.896) (-1700.378) [-1698.090] * (-1708.677) (-1706.403) (-1715.207) [-1703.298] -- 0:00:24
965000 -- (-1719.823) (-1703.983) (-1698.095) [-1699.168] * (-1705.290) (-1709.677) (-1712.619) [-1698.094] -- 0:00:23
Average standard deviation of split frequencies: 0.007828
966000 -- (-1706.695) (-1702.982) [-1702.077] (-1704.192) * [-1695.347] (-1720.678) (-1711.626) (-1705.584) -- 0:00:23
967000 -- (-1701.486) [-1699.365] (-1696.148) (-1710.606) * [-1701.867] (-1696.180) (-1690.024) (-1711.652) -- 0:00:22
968000 -- (-1713.584) [-1703.504] (-1695.606) (-1702.987) * [-1706.349] (-1707.475) (-1710.035) (-1699.249) -- 0:00:21
969000 -- (-1701.798) (-1701.983) [-1694.636] (-1715.744) * [-1709.276] (-1702.260) (-1707.142) (-1703.972) -- 0:00:21
970000 -- (-1725.894) (-1705.661) [-1706.826] (-1717.027) * (-1694.991) [-1705.009] (-1708.778) (-1700.447) -- 0:00:20
Average standard deviation of split frequencies: 0.007829
971000 -- (-1713.053) (-1706.197) [-1705.876] (-1720.861) * [-1706.811] (-1712.233) (-1704.381) (-1699.576) -- 0:00:19
972000 -- (-1703.997) (-1710.649) (-1717.914) [-1711.884] * (-1696.918) (-1712.562) (-1704.345) [-1698.848] -- 0:00:18
973000 -- (-1707.580) [-1694.430] (-1719.071) (-1711.710) * [-1708.680] (-1716.027) (-1713.817) (-1697.130) -- 0:00:18
974000 -- (-1705.484) [-1698.783] (-1710.413) (-1695.764) * [-1701.478] (-1713.607) (-1698.060) (-1717.559) -- 0:00:17
975000 -- (-1715.239) (-1704.025) (-1698.322) [-1699.470] * (-1703.076) (-1714.278) (-1722.259) [-1706.366] -- 0:00:16
Average standard deviation of split frequencies: 0.007885
976000 -- (-1705.175) (-1705.921) (-1705.719) [-1695.224] * (-1685.732) [-1702.391] (-1709.795) (-1734.610) -- 0:00:16
977000 -- [-1693.112] (-1709.667) (-1712.203) (-1702.158) * [-1694.353] (-1708.931) (-1703.051) (-1708.797) -- 0:00:15
978000 -- (-1706.725) (-1696.843) (-1707.811) [-1710.285] * (-1704.214) (-1720.506) [-1705.653] (-1716.560) -- 0:00:14
979000 -- (-1710.903) (-1697.906) [-1701.512] (-1714.768) * [-1691.788] (-1703.703) (-1709.070) (-1727.687) -- 0:00:14
980000 -- (-1703.921) [-1708.710] (-1703.162) (-1701.491) * (-1698.195) (-1701.736) [-1703.479] (-1720.798) -- 0:00:13
Average standard deviation of split frequencies: 0.007795
981000 -- [-1711.467] (-1701.910) (-1708.301) (-1705.724) * (-1712.999) [-1697.195] (-1702.938) (-1723.175) -- 0:00:12
982000 -- (-1718.358) (-1703.448) [-1705.890] (-1711.999) * (-1698.433) [-1698.212] (-1718.499) (-1718.212) -- 0:00:12
983000 -- (-1705.236) (-1714.304) [-1708.442] (-1720.676) * (-1694.170) (-1698.197) (-1712.952) [-1707.642] -- 0:00:11
984000 -- (-1702.387) [-1680.928] (-1705.869) (-1702.857) * [-1697.943] (-1698.614) (-1712.727) (-1710.919) -- 0:00:10
985000 -- (-1719.179) (-1708.383) (-1708.142) [-1705.987] * (-1700.080) [-1688.008] (-1721.963) (-1710.554) -- 0:00:10
Average standard deviation of split frequencies: 0.007792
986000 -- [-1696.736] (-1714.948) (-1720.123) (-1714.076) * (-1705.906) [-1709.297] (-1709.025) (-1701.740) -- 0:00:09
987000 -- [-1695.454] (-1711.486) (-1706.672) (-1719.405) * (-1694.506) [-1687.503] (-1722.425) (-1712.838) -- 0:00:08
988000 -- (-1700.841) (-1719.098) (-1701.627) [-1694.168] * (-1713.154) (-1718.041) [-1717.556] (-1715.536) -- 0:00:08
989000 -- [-1689.072] (-1704.897) (-1709.441) (-1700.453) * (-1697.097) (-1701.896) (-1705.441) [-1694.447] -- 0:00:07
990000 -- (-1708.706) (-1699.726) [-1708.474] (-1710.173) * (-1710.871) [-1695.317] (-1724.626) (-1697.227) -- 0:00:06
Average standard deviation of split frequencies: 0.007787
991000 -- [-1709.183] (-1713.618) (-1689.415) (-1710.231) * [-1709.260] (-1717.791) (-1706.502) (-1699.488) -- 0:00:06
992000 -- [-1702.500] (-1695.552) (-1711.355) (-1699.830) * (-1709.048) (-1718.154) (-1705.901) [-1694.096] -- 0:00:05
993000 -- (-1699.306) [-1704.770] (-1712.609) (-1719.930) * (-1711.482) (-1711.365) [-1699.834] (-1703.109) -- 0:00:04
994000 -- (-1717.451) [-1709.449] (-1703.677) (-1719.573) * (-1709.840) (-1720.799) (-1694.439) [-1714.947] -- 0:00:04
995000 -- [-1693.290] (-1708.455) (-1708.762) (-1712.550) * (-1715.551) (-1701.215) [-1699.636] (-1709.840) -- 0:00:03
Average standard deviation of split frequencies: 0.007662
996000 -- [-1701.016] (-1721.001) (-1724.714) (-1700.942) * (-1707.094) (-1705.831) [-1697.952] (-1728.730) -- 0:00:02
997000 -- [-1694.449] (-1701.043) (-1712.976) (-1698.227) * (-1704.277) (-1707.397) [-1704.326] (-1726.855) -- 0:00:02
998000 -- (-1702.575) (-1716.875) [-1704.318] (-1701.953) * (-1710.316) (-1707.644) (-1708.913) [-1694.782] -- 0:00:01
999000 -- [-1691.618] (-1731.683) (-1700.549) (-1713.092) * (-1707.954) (-1704.261) [-1696.562] (-1697.485) -- 0:00:00
1000000 -- (-1712.028) [-1697.629] (-1723.033) (-1722.228) * [-1691.432] (-1705.827) (-1705.639) (-1714.123) -- 0:00:00
Average standard deviation of split frequencies: 0.007455
Analysis completed in 11 mins 19 seconds
Analysis used 678.28 seconds of CPU time
Likelihood of best state for "cold" chain of run 1 was -1676.59
Likelihood of best state for "cold" chain of run 2 was -1676.95
Acceptance rates for the moves in the "cold" chain of run 1:
With prob. (last 100) chain accepted proposals by move
49.0 % ( 41 %) Dirichlet(Revmat{all})
70.8 % ( 64 %) Slider(Revmat{all})
25.8 % ( 25 %) Dirichlet(Pi{all})
27.7 % ( 31 %) Slider(Pi{all})
75.2 % ( 54 %) Multiplier(Alpha{1,2})
64.3 % ( 31 %) Multiplier(Alpha{3})
85.8 % ( 76 %) Slider(Pinvar{all})
41.8 % ( 46 %) ExtSPR(Tau{all},V{all})
31.1 % ( 33 %) ExtTBR(Tau{all},V{all})
49.3 % ( 47 %) NNI(Tau{all},V{all})
24.6 % ( 21 %) ParsSPR(Tau{all},V{all})
27.5 % ( 27 %) Multiplier(V{all})
69.1 % ( 70 %) Nodeslider(V{all})
25.7 % ( 29 %) TLMultiplier(V{all})
Acceptance rates for the moves in the "cold" chain of run 2:
With prob. (last 100) chain accepted proposals by move
48.8 % ( 47 %) Dirichlet(Revmat{all})
69.8 % ( 57 %) Slider(Revmat{all})
25.9 % ( 28 %) Dirichlet(Pi{all})
27.8 % ( 25 %) Slider(Pi{all})
76.0 % ( 49 %) Multiplier(Alpha{1,2})
63.7 % ( 34 %) Multiplier(Alpha{3})
85.8 % ( 77 %) Slider(Pinvar{all})
42.2 % ( 41 %) ExtSPR(Tau{all},V{all})
31.2 % ( 34 %) ExtTBR(Tau{all},V{all})
48.9 % ( 58 %) NNI(Tau{all},V{all})
24.2 % ( 19 %) ParsSPR(Tau{all},V{all})
27.4 % ( 20 %) Multiplier(V{all})
68.5 % ( 65 %) Nodeslider(V{all})
25.8 % ( 19 %) TLMultiplier(V{all})
Chain swap information for run 1:
1 2 3 4
----------------------------------
1 | 0.51 0.20 0.07
2 | 166348 0.54 0.24
3 | 166967 166935 0.56
4 | 166925 166093 166732
Chain swap information for run 2:
1 2 3 4
----------------------------------
1 | 0.51 0.21 0.07
2 | 166645 0.54 0.23
3 | 166662 166554 0.56
4 | 166157 167771 166211
Upper diagonal: Proportion of successful state exchanges between chains
Lower diagonal: Number of attempted state exchanges between chains
Chain information:
ID -- Heat
-----------
1 -- 1.00 (cold chain)
2 -- 0.91
3 -- 0.83
4 -- 0.77
Heat = 1 / (1 + T * (ID - 1))
(where T = 0.10 is the temperature and ID is the chain number)
Setting burn-in to 2500
Summarizing parameters in files /data/mrbayes_input.nex.run1.p and /data/mrbayes_input.nex.run2.p
Writing summary statistics to file /data/mrbayes_input.nex.pstat
Using relative burnin ('relburnin=yes'), discarding the first 25 % of samples
Below are rough plots of the generation (x-axis) versus the log
probability of observing the data (y-axis). You can use these
graphs to determine what the burn in for your analysis should be.
When the log probability starts to plateau you may be at station-
arity. Sample trees and parameters after the log probability
plateaus. Of course, this is not a guarantee that you are at sta-
tionarity. Also examine the convergence diagnostics provided by
the 'sump' and 'sumt' commands for all the parameters in your
model. Remember that the burn in is the number of samples to dis-
card. There are a total of ngen / samplefreq samples taken during
a MCMC analysis.
Overlay plot for both runs:
(1 = Run number 1; 2 = Run number 2; * = Both runs)
+------------------------------------------------------------+ -1697.25
| 2 1 1 2 |
| 2 1 |
| 1 |
|1 1 2 2 2 2 1 1 |
| 1 11 22 * 11 2 2 2 1 2|
| 1 2 1 1 11 12 |
| * 2 11 1 1 12 1 1 * |
| 21 2 12 2 1 1 1 1 21 |
| 212 12 121 2 2 2 2 2 * 1 1|
| *22 2 2 1 1 1 2 1 2 2 |
| 1 1 2 1 21 2 2 1 2 2 |
|2 1 21 2 2 2 |
| 1 2 1 1 2 |
| 2 1 2 |
| 2 2 |
+------+-----+-----+-----+-----+-----+-----+-----+-----+-----+ -1703.98
^ ^
250000 1000000
Estimated marginal likelihoods for runs sampled in files
"/data/mrbayes_input.nex.run1.p" and "/data/mrbayes_input.nex.run2.p":
(Use the harmonic mean for Bayes factor comparisons of models)
(Values are saved to the file /data/mrbayes_input.nex.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1688.12 -1715.08
2 -1689.58 -1718.83
--------------------------------------
TOTAL -1688.60 -1718.16
--------------------------------------
Model parameter summaries over the runs sampled in files
"/data/mrbayes_input.nex.run1.p" and "/data/mrbayes_input.nex.run2.p":
Summaries are based on a total of 3002 samples from 2 runs.
Each run produced 2001 samples of which 1501 samples were included.
Parameter summaries saved to file "/data/mrbayes_input.nex.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.120030 0.000253 0.088427 0.149303 0.119003 1024.47 1189.67 1.000
r(A<->C){all} 0.018073 0.000301 0.000003 0.052427 0.013106 487.71 534.06 1.000
r(A<->G){all} 0.204244 0.002232 0.117116 0.297482 0.200120 534.16 578.09 1.000
r(A<->T){all} 0.038181 0.000219 0.012680 0.067539 0.036179 827.33 902.96 1.003
r(C<->G){all} 0.023248 0.000544 0.000005 0.069301 0.016036 582.42 638.27 1.003
r(C<->T){all} 0.628434 0.003234 0.517576 0.734594 0.630819 589.07 625.89 1.001
r(G<->T){all} 0.087819 0.000650 0.038621 0.135669 0.085568 772.95 830.22 1.000
pi(A){all} 0.251390 0.000203 0.222291 0.277740 0.251077 1152.82 1166.98 1.000
pi(C){all} 0.124868 0.000115 0.104527 0.145533 0.124464 1033.74 1089.21 1.000
pi(G){all} 0.197673 0.000169 0.174426 0.224119 0.197007 1118.39 1205.53 1.000
pi(T){all} 0.426070 0.000256 0.396225 0.458055 0.426005 1025.29 1138.20 1.001
alpha{1,2} 0.178722 0.062543 0.000047 0.530809 0.110128 1077.44 1123.65 1.000
alpha{3} 2.055394 1.394859 0.315402 4.359189 1.829020 1174.67 1177.48 1.000
pinvar{all} 0.230526 0.018712 0.000432 0.470827 0.220687 1031.33 1112.79 1.000
------------------------------------------------------------------------------------------------------
* Convergence diagnostic (ESS = Estimated Sample Size); min and avg values
correspond to minimal and average ESS among runs.
ESS value below 100 may indicate that the parameter is undersampled.
+ Convergence diagnostic (PSRF = Potential Scale Reduction Factor; Gelman
and Rubin, 1992) should approach 1.0 as runs converge.
Setting sumt conformat to Simple
Setting urn-in to 2500
Summarizing trees in files "/data/mrbayes_input.nex.run1.t" and "/data/mrbayes_input.nex.run2.t"
Using relative burnin ('relburnin=yes'), discarding the first 25 % of sampled trees
Writing statistics to files /data/mrbayes_input.nex.<parts|tstat|vstat|trprobs|con>
Examining first file ...
Found one tree block in file "/data/mrbayes_input.nex.run1.t" with 2001 trees in last block
Expecting the same number of trees in the last tree block of all files
Tree reading status:
0 10 20 30 40 50 60 70 80 90 100
v-------v-------v-------v-------v-------v-------v-------v-------v-------v-------v
*********************************************************************************
Read a total of 4002 trees in 2 files (sampling 3002 of them)
(Each file contained 2001 trees of which 1501 were sampled)
General explanation:
In an unrooted tree, a taxon bipartition (split) is specified by removing a
branch, thereby dividing the species into those to the left and those to the
right of the branch. Here, taxa to one side of the removed branch are denoted
'.' and those to the other side are denoted '*'. Specifically, the '.' symbol
is used for the taxa on the same side as the outgroup.
In a rooted or clock tree, the tree is rooted using the model and not by
reference to an outgroup. Each bipartition therefore corresponds to a clade,
that is, a group that includes all the descendants of a particular branch in
the tree. Taxa that are included in each clade are denoted using '*', and
taxa that are not included are denoted using the '.' symbol.
The output first includes a key to all the bipartitions with frequency larger
or equual to (Minpartfreq) in at least one run. Minpartfreq is a parameter to
sumt command and currently it is set to 0.10. This is followed by a table
with statistics for the informative bipartitions (those including at least
two taxa), sorted from highest to lowest probability. For each bipartition,
the table gives the number of times the partition or split was observed in all
runs (#obs) and the posterior probability of the bipartition (Probab.), which
is the same as the split frequency. If several runs are summarized, this is
followed by the minimum split frequency (Min(s)), the maximum frequency
(Max(s)), and the standard deviation of frequencies (Stddev(s)) across runs.
The latter value should approach 0 for all bipartitions as MCMC runs converge.
This is followed by a table summarizing branch lengths, node heights (if a
clock model was used) and relaxed clock parameters (if a relaxed clock model
was used). The mean, variance, and 95 % credible interval are given for each
of these parameters. If several runs are summarized, the potential scale
reduction factor (PSRF) is also given; it should approach 1 as runs converge.
Node heights will take calibration points into account, if such points were
used in the analysis.
Note that Stddev may be unreliable if the partition is not present in all
runs (the last column indicates the number of runs that sampled the partition
if more than one run is summarized). The PSRF is not calculated at all if
the partition is not present in all runs.The PSRF is also sensitive to small
sample sizes and it should only be considered a rough guide to convergence
since some of the assumptions allowing one to interpret it as a true potential
scale reduction factor are violated in MrBayes.
List of taxa in bipartitions:
1 -- C216
2 -- C7
3 -- C53
4 -- C113
5 -- C173
6 -- C197
7 -- C242
8 -- C11
9 -- C36
10 -- C57
11 -- C82
12 -- C85
13 -- C78
14 -- C238
15 -- C281
16 -- C60
17 -- C178
18 -- C32
19 -- C71
20 -- C66
21 -- C124
22 -- C65
23 -- C130
24 -- C131
25 -- C72
26 -- C77
27 -- C136
28 -- C93
29 -- C79
30 -- C84
Key to taxon bipartitions (saved to file "/data/mrbayes_input.nex.parts"):
ID -- Partition
-------------------------------------
1 -- .*****************************
2 -- .*............................
3 -- ..*...........................
4 -- ...*..........................
5 -- ....*.........................
6 -- .....*........................
7 -- ......*.......................
8 -- .......*......................
9 -- ........*.....................
10 -- .........*....................
11 -- ..........*...................
12 -- ...........*..................
13 -- ............*.................
14 -- .............*................
15 -- ..............*...............
16 -- ...............*..............
17 -- ................*.............
18 -- .................*............
19 -- ..................*...........
20 -- ...................*..........
21 -- ....................*.........
22 -- .....................*........
23 -- ......................*.......
24 -- .......................*......
25 -- ........................*.....
26 -- .........................*....
27 -- ..........................*...
28 -- ...........................*..
29 -- ............................*.
30 -- .............................*
31 -- ....*...........*.............
32 -- ..................**..........
33 -- .*..**.**.***.****.....*.*****
34 -- ..........***..............***
35 -- .........*............*.......
36 -- .*............**.........**...
37 -- .*.............*.........*....
38 -- .*...*.**.***.**.*.....*.*****
39 -- .*.....**.***.**.*.....*.*****
40 -- ...*..*......*................
41 -- ...*..*......*......*.........
42 -- .**.**.**.***.******.*.*.*****
43 -- .**.**.******.******.***.*****
44 -- ...*.........*................
45 -- .*..**.**.***.******...*.*****
46 -- ..............*...........*...
47 -- .***********************.*****
48 -- .*.............*..............
49 -- .*.......................*....
50 -- .*.............*.........**...
51 -- ...............*.........*....
52 -- .*............**.........*....
53 -- ..*..................*........
54 -- .**.**.******.******.*********
55 -- ...*..*......*......*...*.....
56 -- .**.**.**.***.******...*.*****
57 -- .*..**.**.***.******.*.*.*****
58 -- ..*...............**.*........
59 -- ............*................*
60 -- ...........**..............***
61 -- ..........***...............**
62 -- ..........***..............*.*
63 -- .......**.....................
64 -- ...........**.................
65 -- ............................**
66 -- .................*.....*......
67 -- ........*..............*......
68 -- ......*......*................
69 -- .*.....*......**.........**...
70 -- ...........*...............*..
71 -- .......*...............*......
72 -- ...*..*.......................
73 -- ..........***....*.........***
74 -- ............*..............*..
75 -- ...........*................*.
76 -- ............*...............*.
77 -- .*............**.*.......**...
78 -- ..........**..................
79 -- .......*.........*............
80 -- ..........*..................*
81 -- ...........*.................*
82 -- ..........***..........*...***
83 -- ..........*................*..
84 -- ..........*.................*.
85 -- .*.....**.***.**.*.......*****
86 -- .*............**.......*.**...
87 -- .*.....*..***.**.*.....*.*****
88 -- ...........................**.
89 -- .*........***.**.........*****
90 -- ...........................*.*
91 -- .......*..***..............***
92 -- ..........***..............**.
93 -- ..........*.*..............***
94 -- ........*.***..............***
95 -- ........*........*............
96 -- .*......*.***.**.*.....*.*****
97 -- ..........**...............***
98 -- ...*.........*......*.........
99 -- ..........*.*.................
100 -- .*......*.....**.........**...
101 -- ..*...............**..........
102 -- .......**.***....*.....*...***
103 -- .*.....**.....**.*.....*.**...
104 -- .*.....**.***.**.......*.*****
-------------------------------------
Summary statistics for informative taxon bipartitions
(saved to file "/data/mrbayes_input.nex.tstat"):
ID #obs Probab. Sd(s)+ Min(s) Max(s) Nruns
-----------------------------------------------------------------
31 3002 1.000000 0.000000 1.000000 1.000000 2
32 3002 1.000000 0.000000 1.000000 1.000000 2
33 3002 1.000000 0.000000 1.000000 1.000000 2
34 3002 1.000000 0.000000 1.000000 1.000000 2
35 2980 0.992672 0.000942 0.992005 0.993338 2
36 2963 0.987009 0.003298 0.984677 0.989340 2
37 2921 0.973018 0.000471 0.972685 0.973351 2
38 2895 0.964357 0.003298 0.962025 0.966689 2
39 2716 0.904730 0.002827 0.902732 0.906729 2
40 2676 0.891406 0.015075 0.880746 0.902065 2
41 2621 0.873085 0.000471 0.872751 0.873418 2
42 2617 0.871752 0.008951 0.865423 0.878081 2
43 2571 0.856429 0.017430 0.844104 0.868754 2
44 2123 0.707195 0.023083 0.690873 0.723518 2
45 1762 0.586942 0.014133 0.576949 0.596935 2
46 1028 0.342438 0.008480 0.336442 0.348434 2
47 1014 0.337775 0.018844 0.324450 0.351099 2
48 1008 0.335776 0.015075 0.325117 0.346436 2
49 1001 0.333444 0.003298 0.331113 0.335776 2
50 997 0.332112 0.006124 0.327781 0.336442 2
51 961 0.320120 0.011777 0.311792 0.328448 2
52 959 0.319454 0.013662 0.309793 0.329114 2
53 942 0.313791 0.005653 0.309793 0.317788 2
54 864 0.287808 0.004711 0.284477 0.291139 2
55 798 0.265823 0.016959 0.253831 0.277815 2
56 739 0.246169 0.000471 0.245836 0.246502 2
57 710 0.236509 0.002827 0.234510 0.238508 2
58 441 0.146902 0.000471 0.146569 0.147235 2
59 369 0.122918 0.002355 0.121252 0.124584 2
60 364 0.121252 0.000942 0.120586 0.121919 2
61 362 0.120586 0.000942 0.119920 0.121252 2
62 356 0.118588 0.000942 0.117921 0.119254 2
63 349 0.116256 0.012719 0.107262 0.125250 2
64 347 0.115590 0.001413 0.114590 0.116589 2
65 344 0.114590 0.002827 0.112592 0.116589 2
66 342 0.113924 0.006595 0.109260 0.118588 2
67 342 0.113924 0.009422 0.107262 0.120586 2
68 340 0.113258 0.008480 0.107262 0.119254 2
69 336 0.111925 0.002827 0.109927 0.113924 2
70 335 0.111592 0.008951 0.105263 0.117921 2
71 335 0.111592 0.000471 0.111259 0.111925 2
72 334 0.111259 0.003769 0.108594 0.113924 2
73 334 0.111259 0.000000 0.111259 0.111259 2
74 334 0.111259 0.006595 0.106596 0.115923 2
75 333 0.110926 0.004240 0.107928 0.113924 2
76 332 0.110593 0.018844 0.097268 0.123917 2
77 332 0.110593 0.002827 0.108594 0.112592 2
78 331 0.110260 0.015546 0.099267 0.121252 2
79 330 0.109927 0.007537 0.104597 0.115256 2
80 327 0.108927 0.000471 0.108594 0.109260 2
81 327 0.108927 0.000471 0.108594 0.109260 2
82 326 0.108594 0.008480 0.102598 0.114590 2
83 325 0.108261 0.002355 0.106596 0.109927 2
84 322 0.107262 0.014133 0.097268 0.117255 2
85 320 0.106596 0.015075 0.095936 0.117255 2
86 320 0.106596 0.006595 0.101932 0.111259 2
87 318 0.105929 0.000000 0.105929 0.105929 2
88 317 0.105596 0.012719 0.096602 0.114590 2
89 315 0.104930 0.015546 0.093937 0.115923 2
90 315 0.104930 0.004240 0.101932 0.107928 2
91 315 0.104930 0.001413 0.103931 0.105929 2
92 314 0.104597 0.006595 0.099933 0.109260 2
93 312 0.103931 0.013191 0.094604 0.113258 2
94 311 0.103598 0.013662 0.093937 0.113258 2
95 309 0.102931 0.008009 0.097268 0.108594 2
96 304 0.101266 0.012248 0.092605 0.109927 2
97 304 0.101266 0.012248 0.092605 0.109927 2
98 304 0.101266 0.011306 0.093271 0.109260 2
99 299 0.099600 0.010835 0.091939 0.107262 2
100 296 0.098601 0.011306 0.090606 0.106596 2
101 296 0.098601 0.023555 0.081945 0.115256 2
102 295 0.098268 0.009893 0.091272 0.105263 2
103 292 0.097268 0.011306 0.089274 0.105263 2
104 286 0.095270 0.009422 0.088608 0.101932 2
-----------------------------------------------------------------
+ Convergence diagnostic (standard deviation of split frequencies)
should approach 0.0 as runs converge.
Summary statistics for branch and node parameters
(saved to file "/data/mrbayes_input.nex.vstat"):
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median PSRF+ Nruns
--------------------------------------------------------------------------------------------
length{all}[1] 0.000790 0.000001 0.000000 0.002423 0.000542 1.000 2
length{all}[2] 0.000792 0.000001 0.000000 0.002479 0.000534 1.000 2
length{all}[3] 0.005788 0.000005 0.001986 0.010399 0.005462 1.001 2
length{all}[4] 0.003318 0.000003 0.000445 0.006506 0.003051 1.000 2
length{all}[5] 0.001446 0.000001 0.000001 0.003711 0.001185 1.000 2
length{all}[6] 0.002534 0.000002 0.000198 0.005530 0.002259 1.000 2
length{all}[7] 0.001804 0.000002 0.000079 0.004383 0.001497 1.000 2
length{all}[8] 0.000777 0.000001 0.000000 0.002421 0.000535 1.000 2
length{all}[9] 0.000778 0.000001 0.000000 0.002317 0.000528 1.000 2
length{all}[10] 0.010009 0.000010 0.004438 0.016331 0.009708 1.000 2
length{all}[11] 0.000813 0.000001 0.000000 0.002418 0.000580 1.000 2
length{all}[12] 0.000806 0.000001 0.000000 0.002503 0.000552 1.000 2
length{all}[13] 0.000815 0.000001 0.000001 0.002416 0.000569 1.000 2
length{all}[14] 0.001645 0.000001 0.000039 0.003974 0.001382 1.000 2
length{all}[15] 0.000825 0.000001 0.000000 0.002472 0.000579 1.000 2
length{all}[16] 0.000789 0.000001 0.000000 0.002401 0.000554 1.000 2
length{all}[17] 0.000954 0.000001 0.000000 0.002855 0.000664 1.000 2
length{all}[18] 0.000796 0.000001 0.000001 0.002413 0.000542 1.000 2
length{all}[19] 0.002332 0.000002 0.000191 0.005040 0.002079 1.000 2
length{all}[20] 0.004067 0.000004 0.001049 0.007935 0.003751 1.000 2
length{all}[21] 0.005584 0.000005 0.001697 0.010039 0.005295 1.000 2
length{all}[22] 0.000825 0.000001 0.000000 0.002441 0.000604 1.000 2
length{all}[23] 0.000787 0.000001 0.000000 0.002349 0.000548 1.000 2
length{all}[24] 0.002406 0.000002 0.000206 0.005118 0.002156 1.000 2
length{all}[25] 0.000812 0.000001 0.000000 0.002465 0.000559 1.001 2
length{all}[26] 0.000810 0.000001 0.000000 0.002409 0.000565 1.000 2
length{all}[27] 0.000831 0.000001 0.000001 0.002437 0.000587 1.000 2
length{all}[28] 0.000811 0.000001 0.000001 0.002457 0.000552 1.000 2
length{all}[29] 0.000831 0.000001 0.000000 0.002500 0.000575 1.000 2
length{all}[30] 0.000791 0.000001 0.000000 0.002403 0.000544 1.000 2
length{all}[31] 0.005818 0.000006 0.001592 0.010583 0.005468 1.000 2
length{all}[32] 0.004420 0.000004 0.001076 0.008659 0.004089 1.000 2
length{all}[33] 0.021236 0.000026 0.012175 0.031887 0.020675 1.000 2
length{all}[34] 0.002419 0.000002 0.000274 0.005241 0.002145 1.001 2
length{all}[35] 0.001718 0.000002 0.000076 0.004092 0.001452 1.000 2
length{all}[36] 0.001642 0.000001 0.000044 0.004038 0.001346 1.000 2
length{all}[37] 0.001575 0.000001 0.000014 0.003600 0.001334 1.000 2
length{all}[38] 0.003411 0.000004 0.000158 0.007432 0.003041 1.000 2
length{all}[39] 0.001669 0.000001 0.000026 0.003993 0.001386 1.000 2
length{all}[40] 0.002496 0.000002 0.000209 0.005324 0.002194 1.000 2
length{all}[41] 0.002005 0.000002 0.000004 0.004704 0.001691 1.001 2
length{all}[42] 0.001664 0.000001 0.000038 0.004106 0.001392 1.001 2
length{all}[43] 0.001645 0.000001 0.000021 0.003985 0.001378 1.000 2
length{all}[44] 0.001430 0.000001 0.000001 0.003594 0.001123 1.000 2
length{all}[45] 0.001564 0.000001 0.000001 0.003951 0.001267 1.000 2
length{all}[46] 0.000852 0.000001 0.000002 0.002601 0.000577 1.000 2
length{all}[47] 0.000870 0.000001 0.000003 0.002775 0.000565 1.001 2
length{all}[48] 0.000805 0.000001 0.000000 0.002461 0.000580 1.002 2
length{all}[49] 0.000821 0.000001 0.000001 0.002412 0.000550 1.000 2
length{all}[50] 0.000860 0.000001 0.000002 0.002582 0.000614 1.000 2
length{all}[51] 0.000847 0.000001 0.000001 0.002667 0.000553 1.001 2
length{all}[52] 0.000814 0.000001 0.000001 0.002386 0.000560 0.999 2
length{all}[53] 0.000987 0.000001 0.000000 0.002906 0.000717 0.999 2
length{all}[54] 0.000786 0.000001 0.000000 0.002407 0.000548 0.999 2
length{all}[55] 0.000860 0.000001 0.000003 0.002579 0.000559 1.000 2
length{all}[56] 0.000867 0.000001 0.000000 0.002626 0.000604 1.000 2
length{all}[57] 0.000845 0.000001 0.000000 0.002544 0.000581 0.999 2
length{all}[58] 0.001134 0.000001 0.000004 0.003066 0.000845 1.003 2
length{all}[59] 0.000721 0.000001 0.000001 0.002206 0.000460 1.006 2
length{all}[60] 0.000781 0.000001 0.000008 0.002240 0.000566 0.997 2
length{all}[61] 0.000779 0.000001 0.000002 0.002257 0.000589 0.998 2
length{all}[62] 0.000740 0.000000 0.000000 0.002090 0.000478 0.999 2
length{all}[63] 0.000771 0.000001 0.000001 0.002245 0.000575 0.997 2
length{all}[64] 0.000806 0.000001 0.000000 0.002552 0.000544 0.998 2
length{all}[65] 0.000829 0.000001 0.000008 0.002541 0.000560 1.000 2
length{all}[66] 0.000825 0.000001 0.000002 0.002571 0.000523 0.997 2
length{all}[67] 0.000640 0.000000 0.000000 0.001805 0.000471 0.997 2
length{all}[68] 0.000795 0.000001 0.000006 0.002174 0.000609 1.001 2
length{all}[69] 0.000820 0.000001 0.000001 0.002524 0.000579 1.000 2
length{all}[70] 0.000723 0.000001 0.000003 0.002056 0.000484 0.997 2
length{all}[71] 0.000809 0.000001 0.000001 0.002391 0.000554 1.000 2
length{all}[72] 0.000867 0.000001 0.000002 0.002707 0.000578 0.997 2
length{all}[73] 0.000838 0.000001 0.000001 0.002373 0.000579 0.997 2
length{all}[74] 0.000763 0.000000 0.000001 0.002330 0.000557 0.998 2
length{all}[75] 0.000806 0.000001 0.000002 0.002433 0.000574 0.999 2
length{all}[76] 0.000811 0.000001 0.000004 0.002338 0.000578 1.000 2
length{all}[77] 0.000869 0.000001 0.000003 0.002556 0.000622 1.012 2
length{all}[78] 0.000771 0.000001 0.000002 0.002197 0.000575 1.007 2
length{all}[79] 0.000806 0.000001 0.000001 0.002292 0.000567 0.999 2
length{all}[80] 0.000845 0.000001 0.000000 0.002497 0.000574 0.997 2
length{all}[81] 0.000851 0.000001 0.000001 0.002472 0.000604 0.997 2
length{all}[82] 0.000826 0.000001 0.000001 0.002577 0.000530 1.000 2
length{all}[83] 0.000711 0.000000 0.000005 0.001812 0.000524 1.002 2
length{all}[84] 0.000941 0.000001 0.000003 0.002953 0.000570 0.997 2
length{all}[85] 0.000835 0.000001 0.000004 0.002375 0.000666 1.002 2
length{all}[86] 0.000821 0.000001 0.000007 0.002185 0.000575 1.001 2
length{all}[87] 0.000837 0.000001 0.000005 0.002628 0.000561 0.997 2
length{all}[88] 0.000787 0.000001 0.000003 0.002489 0.000468 0.997 2
length{all}[89] 0.000740 0.000000 0.000005 0.002067 0.000535 1.005 2
length{all}[90] 0.000924 0.000001 0.000005 0.002705 0.000646 0.997 2
length{all}[91] 0.000848 0.000001 0.000002 0.002591 0.000598 0.997 2
length{all}[92] 0.000884 0.000001 0.000010 0.002812 0.000642 1.001 2
length{all}[93] 0.000776 0.000001 0.000011 0.002318 0.000502 0.998 2
length{all}[94] 0.000744 0.000001 0.000006 0.001976 0.000518 1.016 2
length{all}[95] 0.000788 0.000001 0.000001 0.002615 0.000549 0.997 2
length{all}[96] 0.000804 0.000001 0.000007 0.002416 0.000553 0.997 2
length{all}[97] 0.000846 0.000001 0.000000 0.002394 0.000580 1.002 2
length{all}[98] 0.001648 0.000002 0.000093 0.003707 0.001373 0.999 2
length{all}[99] 0.000937 0.000001 0.000002 0.002858 0.000712 0.998 2
length{all}[100] 0.000828 0.000001 0.000000 0.002311 0.000580 0.998 2
length{all}[101] 0.000866 0.000001 0.000003 0.002525 0.000616 1.010 2
length{all}[102] 0.000793 0.000001 0.000001 0.002288 0.000573 1.003 2
length{all}[103] 0.000804 0.000001 0.000009 0.002417 0.000528 0.999 2
length{all}[104] 0.000761 0.000001 0.000004 0.002434 0.000539 0.997 2
--------------------------------------------------------------------------------------------
+ Convergence diagnostic (PSRF = Potential Scale Reduction Factor; Gelman
and Rubin, 1992) should approach 1.0 as runs converge. NA is reported when
deviation of parameter values within all runs is 0 or when a parameter
value (a branch length, for instance) is not sampled in all runs.
Summary statistics for partitions with frequency >= 0.10 in at least one run:
Average standard deviation of split frequencies = 0.007455
Maximum standard deviation of split frequencies = 0.023555
Average PSRF for parameter values (excluding NA and >10.0) = 1.000
Maximum PSRF for parameter values = 1.016
Clade credibility values:
/--------------------------------------------------------------------- C216 (1)
|
|--------------------------------------------------------------------- C72 (25)
|
| /-------- C113 (4)
| /--71--+
| | \-------- C238 (14)
| /---89--+
| | \--------------- C242 (7)
|----------------------87---------------------+
| \----------------------- C124 (21)
|
| /-------- C7 (2)
| |
| /--97--+-------- C60 (16)
| | |
| | \-------- C77 (26)
| /---99--+
| | |--------------- C281 (15)
| | |
| | \--------------- C136 (27)
| |
| |----------------------- C11 (8)
| |
| |----------------------- C36 (9)
| |
| | /-------- C82 (11)
+ | |
| | |-------- C85 (12)
| /---90--+ |
| | | |-------- C78 (13)
| | |------100-----+
| | | |-------- C93 (28)
| | | |
| | | |-------- C79 (29)
| | | |
| /--96--+ | \-------- C84 (30)
| | | |
| | | |----------------------- C32 (18)
| | | |
| | | \----------------------- C131 (24)
| /--100--+ |
| | | \------------------------------- C197 (6)
| | |
| | | /-------- C173 (5)
| /---59--+ \-------------100-------------+
| | | \-------- C178 (17)
| | |
| | | /-------- C71 (19)
| | \-----------------100-----------------+
| /--87--+ \-------- C66 (20)
| | |
| | |------------------------------------------------------ C53 (3)
| | |
\---86--+ \------------------------------------------------------ C65 (22)
|
| /-------- C57 (10)
\-------------------------99-------------------------+
\-------- C130 (23)
Phylogram (based on average branch lengths):
/- C216 (1)
|
|- C72 (25)
|
| /------ C113 (4)
| /--+
| | \--- C238 (14)
| /---+
| | \---- C242 (7)
|---+
| \----------- C124 (21)
|
| /- C7 (2)
| |
| /--+- C60 (16)
| | |
| | \- C77 (26)
| /--+
| | |- C281 (15)
| | |
| | \- C136 (27)
| |
| |- C11 (8)
| |
| |- C36 (9)
| |
| | /- C82 (11)
+ | |
| | |- C85 (12)
| /--+ |
| | | |- C78 (13)
| | |----+
| | | |- C93 (28)
| | | |
| | | |- C79 (29)
| | | |
| /------+ | \- C84 (30)
| | | |
| | | |- C32 (18)
| | | |
| | | \----- C131 (24)
| /-------------------------------------------+ |
| | | \----- C197 (6)
| | |
| | | /--- C173 (5)
| /--+ \-----------+
| | | \-- C178 (17)
| | |
| | | /---- C71 (19)
| | \--------+
| /--+ \-------- C66 (20)
| | |
| | |------------ C53 (3)
| | |
\--+ \- C65 (22)
|
| /--------------------- C57 (10)
\--+
\- C130 (23)
|---------| 0.005 expected changes per site
Calculating tree probabilities...
Credible sets of trees (3002 trees sampled):
50 % credible set contains 1501 trees
90 % credible set contains 2702 trees
95 % credible set contains 2852 trees
99 % credible set contains 2972 trees
Exiting mrbayes block
Reached end of file
Tasks completed, exiting program because mode is noninteractive
To return control to the command line after completion of file processing,
set mode to interactive with 'mb -i <filename>' (i is for interactive)
or use 'set mode=interactive'
-- Starting log on Fri Nov 18 14:40:18 GMT 2022 --
-- Iteration: /working_dir/input/2_modified/DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result--
-- Starting log on Sat Nov 19 11:36:57 GMT 2022 --
-- Iteration: /working_dir/pss_subsets/DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result/original_alignment/codeml,DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result.1--
CODONML in paml version 4.9h, March 2018
----------------------------------------------
Phe F TTT | Ser S TCT | Tyr Y TAT | Cys C TGT
TTC | TCC | TAC | TGC
Leu L TTA | TCA | *** * TAA | *** * TGA
TTG | TCG | TAG | Trp W TGG
----------------------------------------------
Leu L CTT | Pro P CCT | His H CAT | Arg R CGT
CTC | CCC | CAC | CGC
CTA | CCA | Gln Q CAA | CGA
CTG | CCG | CAG | CGG
----------------------------------------------
Ile I ATT | Thr T ACT | Asn N AAT | Ser S AGT
ATC | ACC | AAC | AGC
ATA | ACA | Lys K AAA | Arg R AGA
Met M ATG | ACG | AAG | AGG
----------------------------------------------
Val V GTT | Ala A GCT | Asp D GAT | Gly G GGT
GTC | GCC | GAC | GGC
GTA | GCA | Glu E GAA | GGA
GTG | GCG | GAG | GGG
----------------------------------------------
Nice code, uuh?
NSsites batch run (ncatG as in YNGP2000): 1 2 7 8
processing fasta file
reading seq# 1 C238 861 sites
reading seq# 2 C60 861 sites
reading seq# 3 C281 861 sites
reading seq# 4 C82 861 sites
reading seq# 5 C32 861 sites
reading seq# 6 C178 861 sites
reading seq# 7 C71 861 sites
reading seq# 8 C78 861 sites
reading seq# 9 C93 861 sites
reading seq#10 C66 861 sites
reading seq#11 C7 861 sites
reading seq#12 C216 861 sites
reading seq#13 C53 861 sites
reading seq#14 C124 861 sites
reading seq#15 C65 861 sites
reading seq#16 C173 861 sites
reading seq#17 C113 861 sites
reading seq#18 C197 861 sites
reading seq#19 C131 861 sites
reading seq#20 C130 861 sites
reading seq#21 C11 861 sites
reading seq#22 C242 861 sites
reading seq#23 C77 861 sites
reading seq#24 C136 861 sites
reading seq#25 C72 861 sites
reading seq#26 C57 861 sites
reading seq#27 C36 861 sites
reading seq#28 C84 861 sites
reading seq#29 C79 861 sites
reading seq#30 C85 861 sitesns = 30 ls = 861
Reading sequences, sequential format..
Reading seq # 1: C238
Reading seq # 2: C60
Reading seq # 3: C281
Reading seq # 4: C82
Reading seq # 5: C32
Reading seq # 6: C178
Reading seq # 7: C71
Reading seq # 8: C78
Reading seq # 9: C93
Reading seq #10: C66
Reading seq #11: C7
Reading seq #12: C216
Reading seq #13: C53
Reading seq #14: C124
Reading seq #15: C65
Reading seq #16: C173
Reading seq #17: C113
Reading seq #18: C197
Reading seq #19: C131
Reading seq #20: C130
Reading seq #21: C11
Reading seq #22: C242
Reading seq #23: C77
Reading seq #24: C136
Reading seq #25: C72
Reading seq #26: C57
Reading seq #27: C36
Reading seq #28: C84
Reading seq #29: C79
Reading seq #30: C85
Sequences read..
Counting site patterns.. 0:00
Compressing, 113 patterns at 287 / 287 sites (100.0%), 0:00
Collecting fpatt[] & pose[], 113 patterns at 287 / 287 sites (100.0%), 0:00
Counting codons..
3480 bytes for distance
110288 bytes for conP
9944 bytes for fhK
5000000 bytes for space
Model 1: NearlyNeutral
TREE # 1
(12, 25, (((17, 1), 22), 14), ((((((((11, 2, 23), 3, 24), 21, 27, (4, 30, 8, 9, 29, 28), 5, 19), 18), (16, 6)), (7, 10)), 13, 15), (26, 20))); MP score: 86
882304 bytes for conP, adjusted
1 node(s) used for scaling (Yang 2000 J Mol Evol 51:423-432):
39
0.018786 0.064446 0.021147 0.101973 0.089920 0.037822 0.018971 0.012519 0.085434 0.036634 0.098319 0.084122 0.017402 0.029645 0.054899 0.049252 0.103172 0.084931 0.042937 0.050814 0.096924 0.075887 0.072310 0.028761 0.100433 0.098061 0.102855 0.101142 0.107711 0.107774 0.078026 0.088025 0.013235 0.068452 0.015102 0.101721 0.088427 0.065607 0.044119 0.101762 0.106084 0.026416 0.062724 0.088056 0.067452 0.300000 0.679272 0.295643
ntime & nrate & np: 45 2 48
Bounds (np=48):
0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000100 0.000010 0.000001
50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 999.000000 0.999990 1.000000
Qfactor_NS = 10.755172
np = 48
lnL0 = -2254.733874
Iterating by ming2
Initial: fx= 2254.733874
x= 0.01879 0.06445 0.02115 0.10197 0.08992 0.03782 0.01897 0.01252 0.08543 0.03663 0.09832 0.08412 0.01740 0.02964 0.05490 0.04925 0.10317 0.08493 0.04294 0.05081 0.09692 0.07589 0.07231 0.02876 0.10043 0.09806 0.10285 0.10114 0.10771 0.10777 0.07803 0.08802 0.01324 0.06845 0.01510 0.10172 0.08843 0.06561 0.04412 0.10176 0.10608 0.02642 0.06272 0.08806 0.06745 0.30000 0.67927 0.29564
1 h-m-p 0.0000 0.0001 1674.4685 ++ 2077.000446 m 0.0001 53 | 1/48
2 h-m-p 0.0000 0.0000 2617.1883 ++ 2024.814054 m 0.0000 104 | 2/48
3 h-m-p 0.0000 0.0000 4730.1724 ++ 2006.787092 m 0.0000 155 | 3/48
4 h-m-p 0.0000 0.0000 3123.3268 +CYCYCCC 1991.637112 6 0.0000 217 | 3/48
5 h-m-p 0.0000 0.0000 2644.5980 ++ 1953.102755 m 0.0000 268 | 4/48
6 h-m-p 0.0000 0.0000 335164.3720 +YYCYCC 1950.979143 5 0.0000 327 | 4/48
7 h-m-p 0.0000 0.0000 30248.7045 ++ 1924.663470 m 0.0000 378 | 5/48
8 h-m-p 0.0000 0.0000 1684950.5780 ++ 1878.713456 m 0.0000 429 | 6/48
9 h-m-p 0.0000 0.0000 3311.4818 ++ 1865.249059 m 0.0000 480 | 7/48
10 h-m-p 0.0000 0.0000 2179.0326 ++ 1843.891180 m 0.0000 531 | 8/48
11 h-m-p 0.0000 0.0000 1905.6208 ++ 1832.572262 m 0.0000 582 | 9/48
12 h-m-p 0.0000 0.0000 18000.3597 ++ 1826.001514 m 0.0000 633 | 10/48
13 h-m-p 0.0000 0.0000 460021.4941 ++ 1809.654265 m 0.0000 684 | 11/48
14 h-m-p 0.0000 0.0000 5350.0657 ++ 1802.808857 m 0.0000 735 | 12/48
15 h-m-p 0.0000 0.0000 26936.7743 ++ 1798.110019 m 0.0000 786 | 13/48
16 h-m-p 0.0000 0.0000 374684.4779 ++ 1786.336915 m 0.0000 837 | 14/48
17 h-m-p 0.0000 0.0000 18415.9090 ++ 1783.731143 m 0.0000 888 | 15/48
18 h-m-p 0.0000 0.0000 4222.5405 ++ 1779.581162 m 0.0000 939 | 16/48
19 h-m-p 0.0000 0.0000 4906.7367 ++ 1777.785690 m 0.0000 990 | 17/48
20 h-m-p 0.0000 0.0000 2891.2641 ++ 1773.614910 m 0.0000 1041 | 18/48
21 h-m-p 0.0000 0.0000 856.8131 ++ 1773.578842 m 0.0000 1092 | 19/48
22 h-m-p 0.0000 0.0001 505.8642 ++ 1755.851302 m 0.0001 1143 | 19/48
23 h-m-p 0.0000 0.0000 4028.5943 +YYYCCC 1749.508808 5 0.0000 1202 | 19/48
24 h-m-p 0.0000 0.0000 973.6631 +CYYCCC 1743.542847 5 0.0000 1262 | 19/48
25 h-m-p 0.0000 0.0000 2954.1301 +YYYCCC 1736.506158 5 0.0000 1321 | 19/48
26 h-m-p 0.0000 0.0001 1168.9503 +YYCCCC 1729.781051 5 0.0000 1381 | 19/48
27 h-m-p 0.0000 0.0001 615.2820 +YYCCC 1724.871106 4 0.0001 1439 | 19/48
28 h-m-p 0.0000 0.0000 1227.7102 +YCCC 1722.334502 3 0.0000 1496 | 19/48
29 h-m-p 0.0000 0.0000 609.5809 ++ 1719.339808 m 0.0000 1547 | 19/48
30 h-m-p 0.0000 0.0000 758.5337
h-m-p: 0.00000000e+00 0.00000000e+00 7.58533700e+02 1719.339808
.. | 19/48
31 h-m-p 0.0000 0.0001 34265.1191 -YCYYYYC 1712.267575 6 0.0000 1654 | 19/48
32 h-m-p 0.0000 0.0001 1285.2872 YCYCCC 1705.672227 5 0.0000 1713 | 19/48
33 h-m-p 0.0000 0.0000 639.9984 +YCYYYCC 1695.607704 6 0.0000 1773 | 19/48
34 h-m-p 0.0000 0.0000 2326.9510 +YYYYCC 1693.336816 5 0.0000 1831 | 19/48
35 h-m-p 0.0000 0.0000 5156.3407 +YYYCCCCC 1690.047027 7 0.0000 1894 | 19/48
36 h-m-p 0.0000 0.0000 2045.7217 +YCYYCCC 1682.763323 6 0.0000 1955 | 19/48
37 h-m-p 0.0000 0.0000 719.1200 +YYYCCC 1680.954062 5 0.0000 2014 | 19/48
38 h-m-p 0.0000 0.0000 3484.7576 +YYYYCYCCC 1676.564414 8 0.0000 2077 | 19/48
39 h-m-p 0.0000 0.0000 261.2794 YCYCCC 1675.936644 5 0.0000 2136 | 19/48
40 h-m-p 0.0000 0.0002 583.9657 ++YCCC 1669.620888 3 0.0001 2194 | 19/48
41 h-m-p 0.0000 0.0001 577.6756 +YC 1667.980664 1 0.0000 2247 | 19/48
42 h-m-p 0.0000 0.0001 439.4738 +CYC 1666.085403 2 0.0001 2302 | 19/48
43 h-m-p 0.0000 0.0000 995.1708 ++ 1665.270426 m 0.0000 2353 | 19/48
44 h-m-p 0.0000 0.0001 778.4020 YCCCC 1663.957578 4 0.0000 2411 | 19/48
45 h-m-p 0.0000 0.0001 566.6579 YCCC 1662.771301 3 0.0000 2467 | 19/48
46 h-m-p 0.0000 0.0002 336.3782 YCCC 1661.900909 3 0.0001 2523 | 19/48
47 h-m-p 0.0000 0.0002 603.8231 +YYCCCC 1659.688834 5 0.0001 2583 | 19/48
48 h-m-p 0.0000 0.0001 2356.2211 CYCC 1658.349865 3 0.0000 2639 | 19/48
49 h-m-p 0.0001 0.0006 343.2321 YCCCC 1655.135938 4 0.0003 2697 | 19/48
50 h-m-p 0.0000 0.0002 686.0843 YCCC 1654.044931 3 0.0001 2753 | 19/48
51 h-m-p 0.0001 0.0003 500.4122 YCCCC 1652.058120 4 0.0001 2811 | 19/48
52 h-m-p 0.0000 0.0002 569.2973 YCYCCC 1650.677332 5 0.0001 2870 | 19/48
53 h-m-p 0.0001 0.0004 880.8762 +YYCCC 1646.405119 4 0.0002 2928 | 19/48
54 h-m-p 0.0000 0.0002 956.9692 YCCCC 1643.801116 4 0.0001 2986 | 19/48
55 h-m-p 0.0000 0.0001 870.3455 YCCC 1643.402551 3 0.0000 3042 | 19/48
56 h-m-p 0.0000 0.0002 80.2586 YYC 1643.347863 2 0.0000 3095 | 19/48
57 h-m-p 0.0004 0.0049 7.6498 CC 1643.343524 1 0.0001 3148 | 19/48
58 h-m-p 0.0003 0.0132 2.5908 CC 1643.333856 1 0.0005 3201 | 19/48
59 h-m-p 0.0002 0.0533 5.0761 +++YCCYCC 1637.479153 5 0.0418 3264 | 19/48
60 h-m-p 0.0001 0.0004 208.2664 CCC 1637.058528 2 0.0001 3319 | 19/48
61 h-m-p 0.0320 1.2066 0.5752 ++CYCCC 1631.819894 4 0.6830 3379 | 19/48
62 h-m-p 0.5487 2.7433 0.3396 +YCCCC 1626.799822 4 1.4833 3467 | 19/48
63 h-m-p 0.3670 1.8348 0.5606 +YCCCC 1623.034740 4 0.9621 3555 | 19/48
64 h-m-p 0.3533 1.7664 0.4317 +YCCCC 1620.390501 4 1.0309 3643 | 19/48
65 h-m-p 0.3412 1.7061 0.2956 YCCC 1619.456540 3 0.6429 3728 | 19/48
66 h-m-p 0.5300 4.3045 0.3586 +YCC 1618.332294 2 1.4933 3812 | 19/48
67 h-m-p 0.7897 3.9487 0.4631 YCCC 1617.508854 3 1.3796 3897 | 19/48
68 h-m-p 0.5676 2.8380 0.6287 YCCC 1616.939198 3 1.0483 3982 | 19/48
69 h-m-p 1.4180 7.0901 0.3637 CCC 1616.746472 2 1.1184 4066 | 19/48
70 h-m-p 1.6000 8.0000 0.2130 CYC 1616.650125 2 1.8467 4149 | 19/48
71 h-m-p 1.6000 8.0000 0.0944 YCC 1616.581028 2 2.8078 4232 | 19/48
72 h-m-p 1.6000 8.0000 0.0307 +YCCC 1616.431718 3 4.6114 4318 | 19/48
73 h-m-p 1.6000 8.0000 0.0716 CCC 1616.367436 2 1.6300 4402 | 19/48
74 h-m-p 1.6000 8.0000 0.0207 CCC 1616.339983 2 1.8389 4486 | 19/48
75 h-m-p 0.9424 8.0000 0.0404 +YC 1616.311628 1 2.7827 4568 | 19/48
76 h-m-p 1.6000 8.0000 0.0080 +YC 1616.236329 1 4.9387 4650 | 19/48
77 h-m-p 0.3578 8.0000 0.1103 +CCCC 1616.135399 3 2.5168 4737 | 19/48
78 h-m-p 1.6000 8.0000 0.1233 YCC 1616.114440 2 1.1030 4820 | 19/48
79 h-m-p 1.6000 8.0000 0.0195 CY 1616.108623 1 1.4667 4902 | 19/48
80 h-m-p 1.6000 8.0000 0.0017 C 1616.105575 0 1.6480 4982 | 19/48
81 h-m-p 0.2281 8.0000 0.0120 +YC 1616.103581 1 2.2311 5064 | 19/48
82 h-m-p 1.6000 8.0000 0.0047 YC 1616.101765 1 2.6957 5145 | 19/48
83 h-m-p 1.6000 8.0000 0.0018 C 1616.101305 0 1.5231 5225 | 19/48
84 h-m-p 0.8319 8.0000 0.0034 YC 1616.101196 1 1.4390 5306 | 19/48
85 h-m-p 1.6000 8.0000 0.0009 C 1616.101165 0 1.4235 5386 | 19/48
86 h-m-p 1.6000 8.0000 0.0000 C 1616.101158 0 1.9418 5466 | 19/48
87 h-m-p 1.2759 8.0000 0.0001 C 1616.101155 0 2.0102 5546 | 19/48
88 h-m-p 0.6752 8.0000 0.0002 Y 1616.101155 0 1.6470 5626 | 19/48
89 h-m-p 1.6000 8.0000 0.0001 C 1616.101155 0 1.5508 5706 | 19/48
90 h-m-p 1.6000 8.0000 0.0000 --C 1616.101155 0 0.0250 5788 | 19/48
91 h-m-p 0.0208 8.0000 0.0001 ---C 1616.101155 0 0.0001 5871
Out..
lnL = -1616.101155
5872 lfun, 17616 eigenQcodon, 528480 P(t)
end of tree file.
Time used: 3:07
Model 2: PositiveSelection
TREE # 1
(12, 25, (((17, 1), 22), 14), ((((((((11, 2, 23), 3, 24), 21, 27, (4, 30, 8, 9, 29, 28), 5, 19), 18), (16, 6)), (7, 10)), 13, 15), (26, 20))); MP score: 86
1 node(s) used for scaling (Yang 2000 J Mol Evol 51:423-432):
39
0.080669 0.061616 0.068082 0.050365 0.109661 0.061906 0.095774 0.038016 0.013417 0.039001 0.077069 0.098609 0.018922 0.045420 0.067332 0.100878 0.052391 0.101089 0.039923 0.057057 0.103720 0.084664 0.044145 0.070410 0.043181 0.010309 0.055291 0.036173 0.063795 0.044612 0.027713 0.038112 0.097829 0.093317 0.036855 0.057863 0.030860 0.062576 0.071192 0.089256 0.011817 0.074395 0.010007 0.024812 0.032474 6.172672 1.609710 0.539730 0.286354 1.338501
ntime & nrate & np: 45 3 50
Bounds (np=50):
0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000100 -99.000000 -99.000000 0.000001 1.000000
50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 999.000000 99.000000 99.000000 1.000000 999.000000
Qfactor_NS = 2.835595
np = 50
lnL0 = -2095.938055
Iterating by ming2
Initial: fx= 2095.938055
x= 0.08067 0.06162 0.06808 0.05037 0.10966 0.06191 0.09577 0.03802 0.01342 0.03900 0.07707 0.09861 0.01892 0.04542 0.06733 0.10088 0.05239 0.10109 0.03992 0.05706 0.10372 0.08466 0.04414 0.07041 0.04318 0.01031 0.05529 0.03617 0.06379 0.04461 0.02771 0.03811 0.09783 0.09332 0.03685 0.05786 0.03086 0.06258 0.07119 0.08926 0.01182 0.07440 0.01001 0.02481 0.03247 6.17267 1.60971 0.53973 0.28635 1.33850
1 h-m-p 0.0000 0.0001 1534.0650 ++ 2000.344428 m 0.0001 55 | 1/50
2 h-m-p 0.0000 0.0000 2497.0008 ++ 1887.606247 m 0.0000 108 | 2/50
3 h-m-p 0.0000 0.0000 7989.8027 ++ 1859.541421 m 0.0000 161 | 3/50
4 h-m-p 0.0000 0.0000 7273055.7314 ++ 1843.139381 m 0.0000 214 | 4/50
5 h-m-p 0.0000 0.0000 6714.6126 ++ 1842.889706 m 0.0000 267 | 5/50
6 h-m-p 0.0000 0.0000 1014.6180 ++ 1835.966011 m 0.0000 320 | 6/50
7 h-m-p 0.0000 0.0000 1069.2447 ++ 1830.648704 m 0.0000 373 | 7/50
8 h-m-p 0.0000 0.0000 1965.8429 ++ 1818.523741 m 0.0000 426 | 8/50
9 h-m-p 0.0000 0.0000 4569.1797 ++ 1816.892331 m 0.0000 479 | 9/50
10 h-m-p 0.0000 0.0000 17561.2250 ++ 1788.767134 m 0.0000 532 | 10/50
11 h-m-p 0.0000 0.0000 2600.8836 ++ 1785.969839 m 0.0000 585 | 11/50
12 h-m-p 0.0000 0.0000 2168.8980 ++ 1769.323357 m 0.0000 638 | 12/50
13 h-m-p 0.0000 0.0000 1338.3346 ++ 1766.554275 m 0.0000 691 | 13/50
14 h-m-p 0.0000 0.0000 1821.8755 ++ 1757.899448 m 0.0000 744 | 14/50
15 h-m-p 0.0000 0.0000 1876.1245 ++ 1740.462226 m 0.0000 797 | 15/50
16 h-m-p 0.0000 0.0000 4701.2980 ++ 1735.256940 m 0.0000 850 | 16/50
17 h-m-p 0.0000 0.0000 1790.5636 ++ 1733.628762 m 0.0000 903 | 17/50
18 h-m-p 0.0000 0.0000 2576.1779 ++ 1717.194187 m 0.0000 956 | 18/50
19 h-m-p 0.0000 0.0000 1097.1941 ++ 1714.291767 m 0.0000 1009 | 19/50
20 h-m-p 0.0000 0.0001 995.1772 ++ 1697.484216 m 0.0001 1062 | 19/50
21 h-m-p 0.0000 0.0000 2895.6912 CCCC 1697.151384 3 0.0000 1121 | 19/50
22 h-m-p 0.0000 0.0000 719.3351 +YYCC 1695.611033 3 0.0000 1179 | 19/50
23 h-m-p 0.0000 0.0000 530.1660 ++ 1693.720459 m 0.0000 1232 | 19/50
24 h-m-p 0.0000 0.0000 2755.1600 +YYYCCC 1688.723980 5 0.0000 1293 | 19/50
25 h-m-p 0.0000 0.0000 401.1287 +YCYCCC 1687.327048 5 0.0000 1355 | 19/50
26 h-m-p 0.0000 0.0000 693.3527 +YYCCCC 1685.731398 5 0.0000 1417 | 19/50
27 h-m-p 0.0000 0.0000 1353.1970 +YCYCCC 1685.044397 5 0.0000 1479 | 19/50
28 h-m-p 0.0000 0.0001 523.8048 ++ 1678.754514 m 0.0001 1532 | 19/50
29 h-m-p -0.0000 -0.0000 311.1770
h-m-p: -4.20481842e-20 -2.10240921e-19 3.11176964e+02 1678.754514
.. | 19/50
30 h-m-p 0.0000 0.0001 115200.5629 --YCYYYCYCCC 1671.238858 9 0.0000 1650 | 19/50
31 h-m-p 0.0000 0.0001 1831.1320 CYCCC 1665.128225 4 0.0000 1710 | 19/50
32 h-m-p 0.0000 0.0001 526.0745 +YYCYCCC 1655.557121 6 0.0001 1773 | 19/50
33 h-m-p 0.0000 0.0000 2066.1870 +YYCYYCCC 1648.325599 7 0.0000 1837 | 19/50
34 h-m-p 0.0000 0.0000 1103.0651 +YYYCCC 1643.854002 5 0.0000 1898 | 18/50
35 h-m-p 0.0000 0.0000 8069.7451 YCCCC 1642.358197 4 0.0000 1958 | 18/50
36 h-m-p 0.0000 0.0000 564.0318 ++ 1641.375824 m 0.0000 2011 | 19/50
37 h-m-p 0.0000 0.0000 539.1396 YCYCCC 1640.800601 5 0.0000 2072 | 19/50
38 h-m-p 0.0000 0.0001 402.9986 YCCCC 1639.887576 4 0.0000 2132 | 19/50
39 h-m-p 0.0000 0.0002 189.8644 CC 1639.493276 1 0.0000 2187 | 19/50
40 h-m-p 0.0000 0.0002 237.3906 CCCC 1638.900171 3 0.0001 2246 | 19/50
41 h-m-p 0.0000 0.0004 350.1402 +CCYC 1634.926103 3 0.0003 2306 | 19/50
42 h-m-p 0.0000 0.0000 3757.9851 ++ 1631.020643 m 0.0000 2359 | 20/50
43 h-m-p 0.0002 0.0011 31.8105 YCC 1630.944043 2 0.0002 2415 | 20/50
44 h-m-p 0.0001 0.0005 63.8195 CCCC 1630.706418 3 0.0001 2474 | 20/50
45 h-m-p 0.0000 0.0002 99.3338 YCYCCC 1630.229600 5 0.0001 2535 | 20/50
46 h-m-p 0.0000 0.0002 292.0816 +YCCC 1628.874014 3 0.0001 2594 | 20/50
47 h-m-p 0.0000 0.0002 518.8041 CCCCC 1627.310808 4 0.0001 2655 | 20/50
48 h-m-p 0.0000 0.0001 255.6734 YCCCC 1626.743808 4 0.0000 2715 | 20/50
49 h-m-p 0.0000 0.0002 207.6289 CCCC 1626.414636 3 0.0000 2774 | 20/50
50 h-m-p 0.0000 0.0002 109.0912 YCC 1626.327523 2 0.0000 2830 | 20/50
51 h-m-p 0.0001 0.0006 45.1206 YC 1626.296749 1 0.0001 2884 | 20/50
52 h-m-p 0.0000 0.0024 80.3139 +YC 1626.053959 1 0.0003 2939 | 20/50
53 h-m-p 0.0001 0.0019 231.0120 +CCC 1624.825147 2 0.0007 2997 | 20/50
54 h-m-p 0.0001 0.0003 1718.0558 +YCCCC 1621.779164 4 0.0002 3058 | 20/50
55 h-m-p 0.0001 0.0005 761.8652 CCCCC 1620.812690 4 0.0002 3119 | 20/50
56 h-m-p 0.0000 0.0002 179.6451 YYY 1620.754458 2 0.0000 3174 | 20/50
57 h-m-p 0.0007 0.0034 8.1074 YC 1620.750881 1 0.0001 3228 | 19/50
58 h-m-p 0.0001 0.0334 27.4419 +CCC 1620.657645 2 0.0003 3286 | 19/50
59 h-m-p 0.0011 0.0235 6.3397 YC 1620.652713 1 0.0002 3340 | 19/50
60 h-m-p 0.0004 0.0219 3.2027 +++ 1620.154807 m 0.0219 3394 | 20/50
61 h-m-p 0.0085 0.2965 1.2245 +++ 1617.641076 m 0.2965 3448 | 21/50
62 h-m-p 0.4377 2.1883 0.2117 CCC 1616.976769 2 0.6921 3505 | 20/50
63 h-m-p 0.0007 0.0036 90.6430 YCCC 1616.862721 3 0.0004 3592 | 20/50
64 h-m-p 0.2883 3.5896 0.1222 +YCC 1616.618429 2 0.8075 3649 | 20/50
65 h-m-p 0.5943 7.7797 0.1661 CCC 1616.453901 2 0.9457 3736 | 20/50
66 h-m-p 1.2478 6.2391 0.0672 YCC 1616.411277 2 0.7800 3822 | 20/50
67 h-m-p 1.5005 8.0000 0.0349 YC 1616.397612 1 0.8239 3906 | 20/50
68 h-m-p 1.6000 8.0000 0.0109 YC 1616.394217 1 0.8638 3990 | 20/50
69 h-m-p 1.4676 8.0000 0.0064 C 1616.392013 0 1.4291 4073 | 20/50
70 h-m-p 1.1215 8.0000 0.0082 YC 1616.386266 1 2.5354 4157 | 20/50
71 h-m-p 1.5101 8.0000 0.0137 CC 1616.369625 1 2.3489 4242 | 20/50
72 h-m-p 1.6000 8.0000 0.0139 YC 1616.331349 1 2.6201 4326 | 20/50
73 h-m-p 1.6000 8.0000 0.0154 YCCC 1616.238785 3 2.8180 4414 | 20/50
74 h-m-p 0.8390 5.4125 0.0517 CCCC 1616.158342 3 1.1364 4503 | 20/50
75 h-m-p 1.4631 8.0000 0.0401 YCC 1616.116088 2 0.9598 4589 | 20/50
76 h-m-p 1.6000 8.0000 0.0225 YC 1616.103956 1 1.0573 4673 | 20/50
77 h-m-p 1.6000 8.0000 0.0061 YC 1616.102254 1 0.9707 4757 | 20/50
78 h-m-p 1.0977 8.0000 0.0054 CC 1616.101484 1 1.6754 4842 | 20/50
79 h-m-p 1.6000 8.0000 0.0040 YC 1616.101202 1 1.1386 4926 | 20/50
80 h-m-p 1.6000 8.0000 0.0021 YC 1616.101158 1 0.8144 5010 | 20/50
81 h-m-p 1.6000 8.0000 0.0005 Y 1616.101155 0 0.8765 5093 | 20/50
82 h-m-p 1.6000 8.0000 0.0001 Y 1616.101155 0 0.9299 5176 | 20/50
83 h-m-p 1.6000 8.0000 0.0001 Y 1616.101155 0 1.0994 5259 | 20/50
84 h-m-p 1.6000 8.0000 0.0000 C 1616.101155 0 2.0568 5342 | 20/50
85 h-m-p 1.6000 8.0000 0.0000 Y 1616.101155 0 1.0354 5425 | 20/50
86 h-m-p 0.6687 8.0000 0.0000 C 1616.101155 0 0.5958 5508 | 20/50
87 h-m-p 1.0476 8.0000 0.0000 Y 1616.101155 0 0.1432 5591 | 20/50
88 h-m-p 0.3153 8.0000 0.0000 C 1616.101155 0 0.0715 5674 | 20/50
89 h-m-p 0.0541 8.0000 0.0000 --------------.. | 20/50
90 h-m-p 0.0013 0.6549 0.0110 ----------- | 20/50
91 h-m-p 0.0013 0.6549 0.0110 -----------
Out..
lnL = -1616.101155
5954 lfun, 23816 eigenQcodon, 803790 P(t)
BEBing (dim = 4). This may take several minutes.
Calculating f(x_h|w): 10 categories 21 w sets.
Calculating f(X), the marginal likelihood.
log(fX) = -1625.795243 S = -1557.324259 -94.663508
Calculating f(w|X), posterior probabilities of site classes.
did 10 / 113 patterns 7:52
did 20 / 113 patterns 7:52
did 30 / 113 patterns 7:52
did 40 / 113 patterns 7:52
did 50 / 113 patterns 7:52
did 60 / 113 patterns 7:52
did 70 / 113 patterns 7:52
did 80 / 113 patterns 7:52
did 90 / 113 patterns 7:52
did 100 / 113 patterns 7:52
did 110 / 113 patterns 7:52
did 113 / 113 patterns 7:52end of tree file.
Time used: 7:52
Model 7: beta
TREE # 1
(12, 25, (((17, 1), 22), 14), ((((((((11, 2, 23), 3, 24), 21, 27, (4, 30, 8, 9, 29, 28), 5, 19), 18), (16, 6)), (7, 10)), 13, 15), (26, 20))); MP score: 86
1 node(s) used for scaling (Yang 2000 J Mol Evol 51:423-432):
39
0.077599 0.102285 0.108572 0.099658 0.108843 0.013852 0.092800 0.025144 0.097658 0.027544 0.056399 0.018258 0.102141 0.013357 0.061731 0.098083 0.039620 0.063895 0.016833 0.024067 0.012740 0.079278 0.048333 0.017794 0.027257 0.025380 0.084039 0.041689 0.056216 0.076361 0.087382 0.083096 0.080204 0.027399 0.060895 0.067159 0.108366 0.038584 0.010937 0.096954 0.059865 0.045896 0.040820 0.094306 0.060486 6.172735 0.602135 1.045517
ntime & nrate & np: 45 1 48
Bounds (np=48):
0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000100 0.005000 0.005000
50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 999.000000 99.000000 99.000000
Qfactor_NS = 3.810536
np = 48
lnL0 = -2023.100559
Iterating by ming2
Initial: fx= 2023.100559
x= 0.07760 0.10228 0.10857 0.09966 0.10884 0.01385 0.09280 0.02514 0.09766 0.02754 0.05640 0.01826 0.10214 0.01336 0.06173 0.09808 0.03962 0.06390 0.01683 0.02407 0.01274 0.07928 0.04833 0.01779 0.02726 0.02538 0.08404 0.04169 0.05622 0.07636 0.08738 0.08310 0.08020 0.02740 0.06089 0.06716 0.10837 0.03858 0.01094 0.09695 0.05987 0.04590 0.04082 0.09431 0.06049 6.17273 0.60213 1.04552
1 h-m-p 0.0000 0.0001 977.6288 ++ 1953.952133 m 0.0001 101 | 1/48
2 h-m-p 0.0000 0.0000 7151.3050 ++ 1930.827847 m 0.0000 200 | 2/48
3 h-m-p 0.0000 0.0000 2447.7659 ++ 1924.643512 m 0.0000 298 | 3/48
4 h-m-p 0.0000 0.0000 1050.1409 ++ 1909.137264 m 0.0000 395 | 3/48
5 h-m-p 0.0000 0.0000 2434.8436 ++ 1891.629958 m 0.0000 491 | 4/48
6 h-m-p 0.0000 0.0000 1375.2945 ++ 1884.593321 m 0.0000 587 | 5/48
7 h-m-p 0.0000 0.0000 2927.9015 ++ 1828.208100 m 0.0000 682 | 5/48
8 h-m-p 0.0000 0.0000 42035.6303 ++ 1810.049231 m 0.0000 776 | 6/48
9 h-m-p 0.0000 0.0000 4436.4646 ++ 1782.907428 m 0.0000 870 | 7/48
10 h-m-p 0.0000 0.0000 31213.7289 ++ 1762.707234 m 0.0000 963 | 8/48
11 h-m-p 0.0000 0.0000 749976.6385 ++ 1756.613598 m 0.0000 1055 | 9/48
12 h-m-p 0.0000 0.0000 11512.4507 ++ 1736.102701 m 0.0000 1146 | 10/48
13 h-m-p 0.0000 0.0000 17455.9271 ++ 1726.103752 m 0.0000 1236 | 10/48
14 h-m-p 0.0000 0.0000 47462.1564
h-m-p: 6.29587083e-24 3.14793541e-23 4.74621564e+04 1726.103752
.. | 10/48
15 h-m-p 0.0000 0.0000 3223.7805 YCYCCC 1719.388027 5 0.0000 1419 | 10/48
16 h-m-p 0.0000 0.0000 892.8847 ++ 1706.558895 m 0.0000 1508 | 11/48
17 h-m-p 0.0000 0.0000 35769.1850 ++ 1699.005427 m 0.0000 1597 | 12/48
18 h-m-p 0.0000 0.0000 170846.0044 ++ 1688.944635 m 0.0000 1685 | 13/48
19 h-m-p 0.0000 0.0000 5451.0640 ++ 1681.884201 m 0.0000 1772 | 14/48
20 h-m-p 0.0000 0.0000 2135.3081 ++ 1680.996964 m 0.0000 1858 | 15/48
21 h-m-p 0.0000 0.0000 2259.0857 ++ 1678.410770 m 0.0000 1943 | 16/48
22 h-m-p 0.0000 0.0000 3434.8895 ++ 1676.595880 m 0.0000 2027 | 17/48
23 h-m-p 0.0000 0.0000 5869.6398 ++ 1671.324785 m 0.0000 2110 | 17/48
24 h-m-p 0.0000 0.0000 4699.2492 ++ 1653.355820 m 0.0000 2192 | 18/48
25 h-m-p 0.0000 0.0000 617.0223 +CYCCC 1647.304029 4 0.0000 2282 | 18/48
26 h-m-p 0.0000 0.0000 760.5215 ++ 1646.262965 m 0.0000 2363 | 19/48
27 h-m-p 0.0000 0.0000 912.8022 YCYCCC 1645.073320 5 0.0000 2452 | 19/48
28 h-m-p 0.0000 0.0000 410.5937 YCCCC 1644.650390 4 0.0000 2539 | 19/48
29 h-m-p 0.0000 0.0001 379.6787 +CYCCC 1642.208066 4 0.0001 2628 | 19/48
30 h-m-p 0.0000 0.0000 2039.4010 CCCC 1640.754380 3 0.0000 2714 | 19/48
31 h-m-p 0.0000 0.0002 592.2810 YCCCCC 1637.284929 5 0.0001 2803 | 19/48
32 h-m-p 0.0000 0.0001 945.6784 +YCCCC 1634.644091 4 0.0000 2891 | 19/48
33 h-m-p 0.0000 0.0001 838.3842 YCCCCC 1631.208027 5 0.0001 2980 | 19/48
34 h-m-p 0.0000 0.0002 172.8697 CCCC 1630.822979 3 0.0000 3066 | 19/48
35 h-m-p 0.0001 0.0008 98.4598 YCCC 1630.443107 3 0.0001 3151 | 19/48
36 h-m-p 0.0000 0.0005 281.2389 +CYCCC 1627.692519 4 0.0003 3240 | 19/48
37 h-m-p 0.0000 0.0001 934.1219 YCCCC 1626.351218 4 0.0000 3327 | 19/48
38 h-m-p 0.0001 0.0005 234.6457 YCC 1626.037409 2 0.0001 3410 | 19/48
39 h-m-p 0.0001 0.0010 114.4976 YCC 1625.913143 2 0.0001 3493 | 19/48
40 h-m-p 0.0002 0.0011 40.7158 CC 1625.877495 1 0.0001 3575 | 19/48
41 h-m-p 0.0003 0.0020 9.1405 CC 1625.874304 1 0.0001 3657 | 19/48
42 h-m-p 0.0001 0.0135 6.1430 ++CCC 1625.808195 2 0.0024 3743 | 19/48
43 h-m-p 0.0001 0.0005 143.7182 YYC 1625.752640 2 0.0001 3825 | 19/48
44 h-m-p 0.0008 0.0064 15.7384 C 1625.741664 0 0.0002 3905 | 19/48
45 h-m-p 0.0001 0.0163 49.9098 +++CYC 1625.138157 2 0.0040 3991 | 19/48
46 h-m-p 0.0001 0.0007 853.8958 YCCC 1624.948312 3 0.0001 4076 | 19/48
47 h-m-p 0.0075 0.0410 8.3920 CCC 1624.729706 2 0.0078 4160 | 19/48
48 h-m-p 0.2140 1.0700 0.1146 YCCCC 1623.599284 4 0.4530 4247 | 19/48
49 h-m-p 0.0325 0.5341 1.5972 +YCCC 1622.921106 3 0.1021 4333 | 19/48
50 h-m-p 0.0564 0.2819 0.3310 YCCCC 1622.604310 4 0.1143 4420 | 19/48
51 h-m-p 0.0490 0.2448 0.0467 YCCCC 1622.202759 4 0.1078 4507 | 19/48
52 h-m-p 0.0184 1.5411 0.2735 +++YYYCCC 1619.809955 5 1.1151 4597 | 19/48
53 h-m-p 0.1732 0.8658 0.4528 +YYYCCC 1617.387541 5 0.6478 4685 | 19/48
54 h-m-p 0.1606 0.8030 0.1578 YCCC 1616.938097 3 0.3144 4770 | 19/48
55 h-m-p 0.1967 1.1848 0.2521 YCCC 1616.288014 3 0.4544 4855 | 19/48
56 h-m-p 0.3343 1.6717 0.0338 CYCCC 1615.829520 4 0.6286 4942 | 19/48
57 h-m-p 0.5341 2.7778 0.0398 CCC 1615.682618 2 0.5446 5026 | 19/48
58 h-m-p 1.5320 8.0000 0.0141 YCC 1615.615114 2 1.0063 5109 | 19/48
59 h-m-p 0.6614 8.0000 0.0215 YC 1615.602092 1 1.1151 5190 | 19/48
60 h-m-p 1.6000 8.0000 0.0037 YC 1615.598598 1 1.0740 5271 | 19/48
61 h-m-p 1.6000 8.0000 0.0020 CC 1615.596751 1 1.4051 5353 | 19/48
62 h-m-p 0.4852 8.0000 0.0057 YC 1615.596170 1 0.8366 5434 | 19/48
63 h-m-p 1.6000 8.0000 0.0012 YC 1615.595938 1 1.1425 5515 | 19/48
64 h-m-p 1.0169 8.0000 0.0013 C 1615.595884 0 1.5236 5595 | 19/48
65 h-m-p 1.6000 8.0000 0.0007 C 1615.595873 0 1.4160 5675 | 19/48
66 h-m-p 1.6000 8.0000 0.0004 Y 1615.595872 0 1.1441 5755 | 19/48
67 h-m-p 1.6000 8.0000 0.0002 Y 1615.595872 0 1.1328 5835 | 19/48
68 h-m-p 1.6000 8.0000 0.0000 Y 1615.595872 0 1.2637 5915 | 19/48
69 h-m-p 1.6000 8.0000 0.0000 C 1615.595872 0 1.7901 5995 | 19/48
70 h-m-p 1.6000 8.0000 0.0000 Y 1615.595872 0 3.0794 6075 | 19/48
71 h-m-p 1.6000 8.0000 0.0000 -Y 1615.595872 0 0.1959 6156 | 19/48
72 h-m-p 0.1426 8.0000 0.0000 C 1615.595872 0 0.1997 6236 | 19/48
73 h-m-p 0.1973 8.0000 0.0000 Y 1615.595872 0 0.1260 6316 | 19/48
74 h-m-p 0.1299 8.0000 0.0000 C 1615.595872 0 0.0325 6396 | 19/48
75 h-m-p 0.0310 8.0000 0.0000 +Y 1615.595872 0 0.1239 6477 | 19/48
76 h-m-p 0.1546 8.0000 0.0000 Y 1615.595872 0 0.1073 6557 | 19/48
77 h-m-p 0.1272 8.0000 0.0000 ---------------.. | 19/48
78 h-m-p 0.0031 1.5352 0.0036 ---Y 1615.595872 0 0.0000 6733 | 19/48
79 h-m-p 0.0160 8.0000 0.0012 --Y 1615.595872 0 0.0001 6815 | 19/48
80 h-m-p 0.0160 8.0000 0.0009 -------------.. | 19/48
81 h-m-p 0.0027 1.3526 0.0044 ------------
Out..
lnL = -1615.595872
6997 lfun, 76967 eigenQcodon, 3148650 P(t)
end of tree file.
Time used: 26:26
Model 8: beta&w>1
TREE # 1
(12, 25, (((17, 1), 22), 14), ((((((((11, 2, 23), 3, 24), 21, 27, (4, 30, 8, 9, 29, 28), 5, 19), 18), (16, 6)), (7, 10)), 13, 15), (26, 20))); MP score: 86
1 node(s) used for scaling (Yang 2000 J Mol Evol 51:423-432):
39
0.089720 0.084059 0.070285 0.108366 0.084876 0.043393 0.020604 0.042237 0.086122 0.010416 0.050127 0.058555 0.082394 0.020195 0.052760 0.090169 0.016013 0.088531 0.035568 0.034960 0.069784 0.047819 0.105634 0.029153 0.068854 0.080855 0.011508 0.086543 0.070735 0.107282 0.050185 0.045831 0.091965 0.052352 0.025541 0.043243 0.094818 0.102715 0.019183 0.102645 0.032513 0.028890 0.109628 0.010310 0.026355 6.109824 0.900000 0.391365 1.407637 1.300000
ntime & nrate & np: 45 2 50
Bounds (np=50):
0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000100 0.000010 0.005000 0.005000 1.000000
50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 50.000000 999.000000 0.999990 99.000000 99.000000 999.000000
Qfactor_NS = 4.107525
np = 50
lnL0 = -2006.402032
Iterating by ming2
Initial: fx= 2006.402032
x= 0.08972 0.08406 0.07028 0.10837 0.08488 0.04339 0.02060 0.04224 0.08612 0.01042 0.05013 0.05856 0.08239 0.02019 0.05276 0.09017 0.01601 0.08853 0.03557 0.03496 0.06978 0.04782 0.10563 0.02915 0.06885 0.08086 0.01151 0.08654 0.07073 0.10728 0.05018 0.04583 0.09197 0.05235 0.02554 0.04324 0.09482 0.10271 0.01918 0.10265 0.03251 0.02889 0.10963 0.01031 0.02635 6.10982 0.90000 0.39137 1.40764 1.30000
1 h-m-p 0.0000 0.0001 1282.4566 ++ 1932.700366 m 0.0001 105 | 1/50
2 h-m-p 0.0000 0.0001 1811.2910 ++ 1847.400310 m 0.0001 208 | 2/50
3 h-m-p 0.0000 0.0000 37137.3171 ++ 1847.121312 m 0.0000 310 | 3/50
4 h-m-p 0.0000 0.0000 1349439.6259 ++ 1842.882816 m 0.0000 411 | 4/50
5 h-m-p 0.0000 0.0000 775674.9851 ++ 1822.781455 m 0.0000 511 | 5/50
6 h-m-p 0.0000 0.0000 12206.9977 ++ 1820.215040 m 0.0000 610 | 6/50
7 h-m-p 0.0000 0.0000 9538.1860 ++ 1779.411274 m 0.0000 708 | 7/50
8 h-m-p 0.0000 0.0000 71563.1462 ++ 1771.399787 m 0.0000 805 | 8/50
9 h-m-p 0.0000 0.0000 25433.0341 ++ 1766.363285 m 0.0000 901 | 9/50
10 h-m-p 0.0000 0.0000 441678.8978 ++ 1763.909352 m 0.0000 996 | 10/50
11 h-m-p 0.0000 0.0000 34776.7516 ++ 1702.913355 m 0.0000 1090 | 11/50
12 h-m-p 0.0000 0.0000 14493.2046 ++ 1700.504399 m 0.0000 1183 | 12/50
13 h-m-p 0.0000 0.0000 8620.6256 ++ 1676.584453 m 0.0000 1275 | 13/50
14 h-m-p 0.0000 0.0000 9030.9595 ++ 1664.926190 m 0.0000 1366 | 14/50
15 h-m-p 0.0000 0.0000 6400.5568 ++ 1664.737094 m 0.0000 1456 | 15/50
16 h-m-p 0.0000 0.0000 3599.5542 ++ 1662.602459 m 0.0000 1545 | 16/50
17 h-m-p 0.0000 0.0000 2244.5086 ++ 1658.185125 m 0.0000 1633 | 17/50
18 h-m-p 0.0000 0.0000 1544.7306 ++ 1648.358661 m 0.0000 1720 | 18/50
19 h-m-p 0.0000 0.0000 1708.7422 ++ 1647.317352 m 0.0000 1806 | 19/50
20 h-m-p 0.0000 0.0001 612.0795 +YCYYCCC 1642.250798 6 0.0000 1901 | 18/50
21 h-m-p 0.0000 0.0000 978.0758 +YYCCC 1639.864877 4 0.0000 1992 | 18/50
22 h-m-p 0.0000 0.0000 520.8780 ++ 1638.903405 m 0.0000 2077 | 19/50
23 h-m-p 0.0000 0.0001 297.5644 YCCCC 1638.275117 4 0.0000 2169 | 19/50
24 h-m-p 0.0000 0.0001 236.7953 CCC 1637.884178 2 0.0000 2257 | 19/50
25 h-m-p 0.0001 0.0003 128.3506 YCCC 1637.003456 3 0.0001 2346 | 19/50
26 h-m-p 0.0000 0.0001 189.8236 YCYCCC 1636.221097 5 0.0001 2438 | 19/50
27 h-m-p 0.0000 0.0001 374.4921 +YCYCCC 1634.831456 5 0.0001 2531 | 19/50
28 h-m-p 0.0001 0.0003 126.9992 CCCC 1634.430833 3 0.0001 2621 | 19/50
29 h-m-p 0.0001 0.0004 160.4305 +YCCC 1633.275818 3 0.0002 2711 | 19/50
30 h-m-p 0.0002 0.0009 196.7227 +YYCCC 1629.004964 4 0.0006 2802 | 19/50
31 h-m-p 0.0000 0.0001 1770.4821 YCCCC 1627.235859 4 0.0000 2893 | 19/50
32 h-m-p 0.0000 0.0001 718.5259 +YCYCCC 1625.783054 5 0.0001 2986 | 19/50
33 h-m-p 0.0001 0.0003 90.5704 CCCC 1625.582191 3 0.0001 3076 | 19/50
34 h-m-p 0.0003 0.0021 23.3408 YC 1625.356014 1 0.0006 3161 | 19/50
35 h-m-p 0.0002 0.0009 52.8128 CYC 1625.236151 2 0.0002 3248 | 19/50
36 h-m-p 0.0003 0.0020 35.1448 +CCC 1624.850090 2 0.0009 3337 | 19/50
37 h-m-p 0.0003 0.0013 71.5292 CC 1624.649922 1 0.0003 3423 | 19/50
38 h-m-p 0.0003 0.0036 60.2670 +CYCCC 1623.476676 4 0.0017 3515 | 19/50
39 h-m-p 0.0007 0.0037 33.7056 +CYC 1622.614610 2 0.0030 3603 | 19/50
40 h-m-p 0.0002 0.0010 25.6643 ++ 1622.237635 m 0.0010 3687 | 20/50
41 h-m-p 0.0015 0.2707 4.0533 ++YCCC 1620.401913 3 0.0512 3778 | 20/50
42 h-m-p 0.0109 0.0544 6.2327 YCCCC 1618.970156 4 0.0246 3868 | 20/50
43 h-m-p 0.0209 0.1043 2.7455 +YYCCCC 1618.000494 5 0.0655 3960 | 20/50
44 h-m-p 0.0284 0.1419 3.0974 CCCC 1617.479188 3 0.0511 4049 | 20/50
45 h-m-p 0.0438 0.2191 2.0379 CCC 1617.264251 2 0.0387 4136 | 20/50
46 h-m-p 0.0178 0.0888 2.1456 YCCCC 1616.988959 4 0.0356 4226 | 20/50
47 h-m-p 0.0676 0.3378 0.5463 CCC 1616.775297 2 0.0727 4313 | 20/50
48 h-m-p 0.0828 0.4141 0.3351 YYC 1616.625992 2 0.0753 4398 | 20/50
49 h-m-p 0.1614 0.8072 0.1498 CCC 1616.359220 2 0.1901 4485 | 20/50
50 h-m-p 0.2120 1.7364 0.1342 C 1616.266970 0 0.2126 4568 | 20/50
51 h-m-p 1.1913 5.9564 0.0230 YCC 1616.097942 2 0.8077 4654 | 20/50
52 h-m-p 0.1877 7.6147 0.0991 YC 1616.059219 1 0.3988 4738 | 20/50
53 h-m-p 0.3630 7.4929 0.1088 YC 1615.986550 1 0.8322 4822 | 20/50
54 h-m-p 1.4363 7.1813 0.0593 YCC 1615.932658 2 1.0762 4908 | 20/50
55 h-m-p 1.6000 8.0000 0.0250 YCC 1615.891865 2 1.0933 4994 | 20/50
56 h-m-p 1.2154 8.0000 0.0225 CC 1615.863387 1 1.0269 5079 | 20/50
57 h-m-p 1.1281 8.0000 0.0205 CC 1615.850258 1 1.6153 5164 | 20/50
58 h-m-p 0.5774 8.0000 0.0574 +CC 1615.836235 1 2.5953 5250 | 20/50
59 h-m-p 1.4343 8.0000 0.1038 +YCCC 1615.805676 3 3.8325 5339 | 20/50
60 h-m-p 0.6909 3.4547 0.4653 YCYYCCC 1615.704718 6 1.4451 5432 | 20/50
61 h-m-p 0.2850 1.4251 0.6564 YCCC 1615.698381 3 0.1369 5520 | 20/50
62 h-m-p 1.1125 6.6244 0.0808 YCC 1615.648899 2 0.6616 5606 | 20/50
63 h-m-p 1.6000 8.0000 0.0214 CC 1615.632689 1 1.4722 5691 | 20/50
64 h-m-p 0.8739 8.0000 0.0361 YC 1615.616616 1 2.1443 5775 | 20/50
65 h-m-p 0.9222 4.6109 0.0311 CCC 1615.608128 2 1.1838 5862 | 20/50
66 h-m-p 0.3330 2.3842 0.1105 CCC 1615.602811 2 0.5428 5949 | 20/50
67 h-m-p 0.8787 4.3936 0.0198 YC 1615.598450 1 2.1768 6033 | 20/50
68 h-m-p 0.6525 3.2623 0.0127 YC 1615.597060 1 1.6300 6117 | 20/50
69 h-m-p 0.7547 3.7736 0.0072 YC 1615.596532 1 1.5828 6201 | 20/50
70 h-m-p 0.1301 0.6507 0.0245 ++ 1615.596199 m 0.6507 6284 | 21/50
71 h-m-p 1.6000 8.0000 0.0025 C 1615.596139 0 0.3568 6367 | 20/50
72 h-m-p 0.0046 2.2806 0.2028 C 1615.596106 0 0.0072 6449 | 20/50
73 h-m-p 0.1673 0.8365 0.0016 ++ 1615.596017 m 0.8365 6532 | 21/50
74 h-m-p 0.0585 8.0000 0.0201 Y 1615.596009 0 0.0254 6615 | 21/50
75 h-m-p 0.1941 8.0000 0.0026 +C 1615.595948 0 1.0829 6698 | 21/50
76 h-m-p 1.6000 8.0000 0.0007 Y 1615.595910 0 3.4891 6780 | 21/50
77 h-m-p 1.6000 8.0000 0.0007 C 1615.595891 0 2.1198 6862 | 21/50
78 h-m-p 1.6000 8.0000 0.0001 C 1615.595876 0 2.0420 6944 | 21/50
79 h-m-p 1.6000 8.0000 0.0001 C 1615.595873 0 2.1547 7026 | 21/50
80 h-m-p 1.6000 8.0000 0.0000 C 1615.595872 0 1.2969 7108 | 21/50
81 h-m-p 0.2466 8.0000 0.0000 +C 1615.595872 0 1.3991 7191 | 21/50
82 h-m-p 1.6000 8.0000 0.0000 C 1615.595872 0 1.6000 7273 | 21/50
83 h-m-p 1.6000 8.0000 0.0000 C 1615.595872 0 0.4000 7355 | 21/50
84 h-m-p 0.3203 8.0000 0.0000 C 1615.595872 0 0.3331 7437 | 21/50
85 h-m-p 0.3379 8.0000 0.0000 C 1615.595872 0 0.0747 7519 | 21/50
86 h-m-p 0.0684 8.0000 0.0000 +Y 1615.595872 0 0.1838 7602 | 21/50
87 h-m-p 0.2006 8.0000 0.0000 C 1615.595872 0 0.0501 7684 | 21/50
88 h-m-p 0.0512 8.0000 0.0000 C 1615.595872 0 0.0512 7766 | 21/50
89 h-m-p 0.0533 8.0000 0.0000 -------------Y 1615.595872 0 0.0000 7861
Out..
lnL = -1615.595872
7862 lfun, 94344 eigenQcodon, 3891690 P(t)
BEBing (dim = 4). This may take several minutes.
Calculating f(x_h|w): 10 categories 20 w sets.
Calculating f(X), the marginal likelihood.
log(fX) = -1625.320412 S = -1557.741097 -98.015452
Calculating f(w|X), posterior probabilities of site classes.
did 10 / 113 patterns 49:19
did 20 / 113 patterns 49:20
did 30 / 113 patterns 49:20
did 40 / 113 patterns 49:20
did 50 / 113 patterns 49:20
did 60 / 113 patterns 49:20
did 70 / 113 patterns 49:20
did 80 / 113 patterns 49:21
did 90 / 113 patterns 49:21
did 100 / 113 patterns 49:21
did 110 / 113 patterns 49:21
did 113 / 113 patterns 49:21end of tree file.
Time used: 49:21
The loglikelihoods for models M1, M2, M7 and M8 are -1616.101155 -1616.101155 -1615.595872 -1615.595872 respectively
CLUSTAL W (1.8) multiple sequence alignment (ALTER 1.3.3)
TCG_22_nsp3_VIPR_ALG4_BBM61464_1_10814_11674_1_2016_12_Japan_Unknown_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
BJ_165_nsp3_VIPR_ALG4_AXX83312_1_10761_11621_1_2015_06_09_China_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
YC_55_nsp3_VIPR_ALG4_AXX83348_1_10761_11621_1_2015_03_12_China_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
HCoV_OC43_Seattle_USA_SC2481_2015_nsp3_VIPR_ALG4_ARU07564_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
5352_2007_nsp3_VIPR_ALG4_701216673_10857_11717_1_2007_05_China_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
OC43_human_USA_901_41_1990_nsp3_VIPR_ALG4_530802215_10838_11698_1_1990_01_17_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
DcCoV_HKU23_camel_Nigeria_NV1385_2016_nsp3_VIPR_ALG4_QEY10662_1_10856_11716_1_2016_01_24_Nigeria_Camel_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
HCoV_OC43_Seattle_USA_SC0810_2019_nsp3_VIPR_ALG4_QEG03753_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
HCoV_OC43_USA_TCNP_00204_2017_nsp3_VIPR_ALG4_ATN39869_1_10849_11709_1_2017_01_03_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
DcCoV_HKU23_camel_Ethiopia_CAC1019_2015_nsp3_VIPR_ALG4_QEY10622_1_10850_11710_1_2015_02_21_Ethiopia_Camel_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
12694_2012_nsp3_VIPR_ALG4_701216743_10857_11717_1_2012_05_China_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
R_AH187_nsp3_VIPR_ALG4_145208950_10842_11702_1_NA_USA_Cattle_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
BCOV_China_SWUN_A10_2018_nsp3_VIPR_ALG4_QOV05174_1_10858_11718_1_2018_11_01_China_Cattle_Betacoronavirus_1 SKRTRLVKGIVCWIMTSTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
IWT_5_nsp3_VIPR_ALG4_BBM60984_1_10834_11694_1_2011_11_Japan_Unknown_Betacoronavirus_1 SKRIRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
DB2_nsp3_VIPR_ALG4_331264482_10843_11703_1_1983_NA_Cattle_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
OC43_human_USA_873_19_1987_nsp3_VIPR_ALG4_530802412_10838_11698_1_1987_03_17_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
IWT_20_nsp3_VIPR_ALG4_BBM61094_1_10834_11694_1_2016_12_Japan_Unknown_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
OC43_human_USA_9612_9_1996_nsp3_VIPR_ALG4_530802204_10838_11698_1_1996_12_04_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
LY341_nsp3_VIPR_ALG4_721347196_10858_11718_1_2011_10_03_China_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCVLCVISLAMLLVK
Kakegawa_nsp3_VIPR_ALG4_155369168_10858_11718_1_NA_Japan_Unknown_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
19572_Belgium_2004_nsp3_VIPR_ALG4_62530899_10858_11718_1_NA_Belgium_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
TCG_26_nsp3_VIPR_ALG4_BBM61504_1_10831_11691_1_2017_12_Japan_Unknown_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
GZYF_26_nsp3_VIPR_ALG4_AXX83330_1_10782_11642_1_2015_05_21_China_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
MDS16_nsp3_VIPR_ALG4_QBQ01836_1_10837_11697_1_NA_NA_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
E_AH187_TC_nsp3_VIPR_ALG4_251748090_10842_11702_1_2000_01_01_USA_Cattle_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
BJ232_nsp3_VIPR_ALG4_AQT26494_1_10791_11651_1_2014_China_Dog_Betacoronavirus_1 SKRIRLFKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVK
5445_2007_nsp3_VIPR_ALG4_701216785_10857_11717_1_2007_06_China_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
HCoV_OC43_Seattle_USA_SC2770_2015_nsp3_VIPR_ALG4_ARK08647_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
HCoV_OC43_Seattle_USA_SC0839_2019_nsp3_VIPR_ALG4_QEG03763_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
HCoV_OC43_Seattle_USA_SC2854_2015_nsp3_VIPR_ALG4_ARU07583_1_10823_11683_1_2015_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVK
*** **.** *****:*************************:*****.************
TCG_22_nsp3_VIPR_ALG4_BBM61464_1_10814_11674_1_2016_12_Japan_Unknown_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
BJ_165_nsp3_VIPR_ALG4_AXX83312_1_10761_11621_1_2015_06_09_China_Unknown_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
YC_55_nsp3_VIPR_ALG4_AXX83348_1_10761_11621_1_2015_03_12_China_Unknown_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
HCoV_OC43_Seattle_USA_SC2481_2015_nsp3_VIPR_ALG4_ARU07564_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
5352_2007_nsp3_VIPR_ALG4_701216673_10857_11717_1_2007_05_China_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
OC43_human_USA_901_41_1990_nsp3_VIPR_ALG4_530802215_10838_11698_1_1990_01_17_USA_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
DcCoV_HKU23_camel_Nigeria_NV1385_2016_nsp3_VIPR_ALG4_QEY10662_1_10856_11716_1_2016_01_24_Nigeria_Camel_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLIVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
HCoV_OC43_Seattle_USA_SC0810_2019_nsp3_VIPR_ALG4_QEG03753_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
HCoV_OC43_USA_TCNP_00204_2017_nsp3_VIPR_ALG4_ATN39869_1_10849_11709_1_2017_01_03_USA_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
DcCoV_HKU23_camel_Ethiopia_CAC1019_2015_nsp3_VIPR_ALG4_QEY10622_1_10850_11710_1_2015_02_21_Ethiopia_Camel_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLIVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
12694_2012_nsp3_VIPR_ALG4_701216743_10857_11717_1_2012_05_China_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
R_AH187_nsp3_VIPR_ALG4_145208950_10842_11702_1_NA_USA_Cattle_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
BCOV_China_SWUN_A10_2018_nsp3_VIPR_ALG4_QOV05174_1_10858_11718_1_2018_11_01_China_Cattle_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
IWT_5_nsp3_VIPR_ALG4_BBM60984_1_10834_11694_1_2011_11_Japan_Unknown_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVDYTYTDEVIYGMLLL
DB2_nsp3_VIPR_ALG4_331264482_10843_11703_1_1983_NA_Cattle_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
OC43_human_USA_873_19_1987_nsp3_VIPR_ALG4_530802412_10838_11698_1_1987_03_17_USA_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
IWT_20_nsp3_VIPR_ALG4_BBM61094_1_10834_11694_1_2016_12_Japan_Unknown_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
OC43_human_USA_9612_9_1996_nsp3_VIPR_ALG4_530802204_10838_11698_1_1996_12_04_USA_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
LY341_nsp3_VIPR_ALG4_721347196_10858_11718_1_2011_10_03_China_Human_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
Kakegawa_nsp3_VIPR_ALG4_155369168_10858_11718_1_NA_Japan_Unknown_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
19572_Belgium_2004_nsp3_VIPR_ALG4_62530899_10858_11718_1_NA_Belgium_Unknown_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
TCG_26_nsp3_VIPR_ALG4_BBM61504_1_10831_11691_1_2017_12_Japan_Unknown_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
GZYF_26_nsp3_VIPR_ALG4_AXX83330_1_10782_11642_1_2015_05_21_China_Unknown_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
MDS16_nsp3_VIPR_ALG4_QBQ01836_1_10837_11697_1_NA_NA_Unknown_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
E_AH187_TC_nsp3_VIPR_ALG4_251748090_10842_11702_1_2000_01_01_USA_Cattle_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
BJ232_nsp3_VIPR_ALG4_AQT26494_1_10791_11651_1_2014_China_Dog_Betacoronavirus_1 HKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
5445_2007_nsp3_VIPR_ALG4_701216785_10857_11717_1_2007_06_China_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
HCoV_OC43_Seattle_USA_SC2770_2015_nsp3_VIPR_ALG4_ARK08647_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
HCoV_OC43_Seattle_USA_SC0839_2019_nsp3_VIPR_ALG4_QEG03763_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
HCoV_OC43_Seattle_USA_SC2854_2015_nsp3_VIPR_ALG4_ARU07583_1_10823_11683_1_2015_USA_Human_Betacoronavirus_1 HKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLL
********** ************:***:*****************:**************
TCG_22_nsp3_VIPR_ALG4_BBM61464_1_10814_11674_1_2016_12_Japan_Unknown_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
BJ_165_nsp3_VIPR_ALG4_AXX83312_1_10761_11621_1_2015_06_09_China_Unknown_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
YC_55_nsp3_VIPR_ALG4_AXX83348_1_10761_11621_1_2015_03_12_China_Unknown_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
HCoV_OC43_Seattle_USA_SC2481_2015_nsp3_VIPR_ALG4_ARU07564_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
5352_2007_nsp3_VIPR_ALG4_701216673_10857_11717_1_2007_05_China_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
OC43_human_USA_901_41_1990_nsp3_VIPR_ALG4_530802215_10838_11698_1_1990_01_17_USA_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
DcCoV_HKU23_camel_Nigeria_NV1385_2016_nsp3_VIPR_ALG4_QEY10662_1_10856_11716_1_2016_01_24_Nigeria_Camel_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
HCoV_OC43_Seattle_USA_SC0810_2019_nsp3_VIPR_ALG4_QEG03753_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
HCoV_OC43_USA_TCNP_00204_2017_nsp3_VIPR_ALG4_ATN39869_1_10849_11709_1_2017_01_03_USA_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
DcCoV_HKU23_camel_Ethiopia_CAC1019_2015_nsp3_VIPR_ALG4_QEY10622_1_10850_11710_1_2015_02_21_Ethiopia_Camel_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
12694_2012_nsp3_VIPR_ALG4_701216743_10857_11717_1_2012_05_China_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
R_AH187_nsp3_VIPR_ALG4_145208950_10842_11702_1_NA_USA_Cattle_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
BCOV_China_SWUN_A10_2018_nsp3_VIPR_ALG4_QOV05174_1_10858_11718_1_2018_11_01_China_Cattle_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
IWT_5_nsp3_VIPR_ALG4_BBM60984_1_10834_11694_1_2011_11_Japan_Unknown_Betacoronavirus_1 TGTVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
DB2_nsp3_VIPR_ALG4_331264482_10843_11703_1_1983_NA_Cattle_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
OC43_human_USA_873_19_1987_nsp3_VIPR_ALG4_530802412_10838_11698_1_1987_03_17_USA_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
IWT_20_nsp3_VIPR_ALG4_BBM61094_1_10834_11694_1_2016_12_Japan_Unknown_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
OC43_human_USA_9612_9_1996_nsp3_VIPR_ALG4_530802204_10838_11698_1_1996_12_04_USA_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
LY341_nsp3_VIPR_ALG4_721347196_10858_11718_1_2011_10_03_China_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
Kakegawa_nsp3_VIPR_ALG4_155369168_10858_11718_1_NA_Japan_Unknown_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
19572_Belgium_2004_nsp3_VIPR_ALG4_62530899_10858_11718_1_NA_Belgium_Unknown_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
TCG_26_nsp3_VIPR_ALG4_BBM61504_1_10831_11691_1_2017_12_Japan_Unknown_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
GZYF_26_nsp3_VIPR_ALG4_AXX83330_1_10782_11642_1_2015_05_21_China_Unknown_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
MDS16_nsp3_VIPR_ALG4_QBQ01836_1_10837_11697_1_NA_NA_Unknown_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
E_AH187_TC_nsp3_VIPR_ALG4_251748090_10842_11702_1_2000_01_01_USA_Cattle_Betacoronavirus_1 IGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALS
BJ232_nsp3_VIPR_ALG4_AQT26494_1_10791_11651_1_2014_China_Dog_Betacoronavirus_1 IGMAFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLVSLFGTYTWTTVLS
5445_2007_nsp3_VIPR_ALG4_701216785_10857_11717_1_2007_06_China_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
HCoV_OC43_Seattle_USA_SC2770_2015_nsp3_VIPR_ALG4_ARK08647_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
HCoV_OC43_Seattle_USA_SC0839_2019_nsp3_VIPR_ALG4_QEG03763_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
HCoV_OC43_Seattle_USA_SC2854_2015_nsp3_VIPR_ALG4_ARU07583_1_10823_11683_1_2015_USA_Human_Betacoronavirus_1 VGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLS
* .********************:***.**** ************.**********.**
TCG_22_nsp3_VIPR_ALG4_BBM61464_1_10814_11674_1_2016_12_Japan_Unknown_Betacoronavirus_1 MAAAKVIAKWVVVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
BJ_165_nsp3_VIPR_ALG4_AXX83312_1_10761_11621_1_2015_06_09_China_Unknown_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
YC_55_nsp3_VIPR_ALG4_AXX83348_1_10761_11621_1_2015_03_12_China_Unknown_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
HCoV_OC43_Seattle_USA_SC2481_2015_nsp3_VIPR_ALG4_ARU07564_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
5352_2007_nsp3_VIPR_ALG4_701216673_10857_11717_1_2007_05_China_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
OC43_human_USA_901_41_1990_nsp3_VIPR_ALG4_530802215_10838_11698_1_1990_01_17_USA_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKVVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
DcCoV_HKU23_camel_Nigeria_NV1385_2016_nsp3_VIPR_ALG4_QEY10662_1_10856_11716_1_2016_01_24_Nigeria_Camel_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
HCoV_OC43_Seattle_USA_SC0810_2019_nsp3_VIPR_ALG4_QEG03753_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
HCoV_OC43_USA_TCNP_00204_2017_nsp3_VIPR_ALG4_ATN39869_1_10849_11709_1_2017_01_03_USA_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
DcCoV_HKU23_camel_Ethiopia_CAC1019_2015_nsp3_VIPR_ALG4_QEY10622_1_10850_11710_1_2015_02_21_Ethiopia_Camel_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
12694_2012_nsp3_VIPR_ALG4_701216743_10857_11717_1_2012_05_China_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
R_AH187_nsp3_VIPR_ALG4_145208950_10842_11702_1_NA_USA_Cattle_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
BCOV_China_SWUN_A10_2018_nsp3_VIPR_ALG4_QOV05174_1_10858_11718_1_2018_11_01_China_Cattle_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
IWT_5_nsp3_VIPR_ALG4_BBM60984_1_10834_11694_1_2011_11_Japan_Unknown_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
DB2_nsp3_VIPR_ALG4_331264482_10843_11703_1_1983_NA_Cattle_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
OC43_human_USA_873_19_1987_nsp3_VIPR_ALG4_530802412_10838_11698_1_1987_03_17_USA_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKVVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
IWT_20_nsp3_VIPR_ALG4_BBM61094_1_10834_11694_1_2016_12_Japan_Unknown_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
OC43_human_USA_9612_9_1996_nsp3_VIPR_ALG4_530802204_10838_11698_1_1996_12_04_USA_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
LY341_nsp3_VIPR_ALG4_721347196_10858_11718_1_2011_10_03_China_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
Kakegawa_nsp3_VIPR_ALG4_155369168_10858_11718_1_NA_Japan_Unknown_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
19572_Belgium_2004_nsp3_VIPR_ALG4_62530899_10858_11718_1_NA_Belgium_Unknown_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
TCG_26_nsp3_VIPR_ALG4_BBM61504_1_10831_11691_1_2017_12_Japan_Unknown_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
GZYF_26_nsp3_VIPR_ALG4_AXX83330_1_10782_11642_1_2015_05_21_China_Unknown_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
MDS16_nsp3_VIPR_ALG4_QBQ01836_1_10837_11697_1_NA_NA_Unknown_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
E_AH187_TC_nsp3_VIPR_ALG4_251748090_10842_11702_1_2000_01_01_USA_Cattle_Betacoronavirus_1 MAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
BJ232_nsp3_VIPR_ALG4_AQT26494_1_10791_11651_1_2014_China_Dog_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
5445_2007_nsp3_VIPR_ALG4_701216785_10857_11717_1_2007_06_China_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
HCoV_OC43_Seattle_USA_SC2770_2015_nsp3_VIPR_ALG4_ARK08647_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
HCoV_OC43_Seattle_USA_SC0839_2019_nsp3_VIPR_ALG4_QEG03763_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
HCoV_OC43_Seattle_USA_SC2854_2015_nsp3_VIPR_ALG4_ARU07583_1_10823_11683_1_2015_USA_Human_Betacoronavirus_1 MAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYN
**.********.*************:**:*******************************
TCG_22_nsp3_VIPR_ALG4_BBM61464_1_10814_11674_1_2016_12_Japan_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
BJ_165_nsp3_VIPR_ALG4_AXX83312_1_10761_11621_1_2015_06_09_China_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
YC_55_nsp3_VIPR_ALG4_AXX83348_1_10761_11621_1_2015_03_12_China_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
HCoV_OC43_Seattle_USA_SC2481_2015_nsp3_VIPR_ALG4_ARU07564_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
5352_2007_nsp3_VIPR_ALG4_701216673_10857_11717_1_2007_05_China_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
OC43_human_USA_901_41_1990_nsp3_VIPR_ALG4_530802215_10838_11698_1_1990_01_17_USA_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
DcCoV_HKU23_camel_Nigeria_NV1385_2016_nsp3_VIPR_ALG4_QEY10662_1_10856_11716_1_2016_01_24_Nigeria_Camel_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
HCoV_OC43_Seattle_USA_SC0810_2019_nsp3_VIPR_ALG4_QEG03753_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
HCoV_OC43_USA_TCNP_00204_2017_nsp3_VIPR_ALG4_ATN39869_1_10849_11709_1_2017_01_03_USA_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
DcCoV_HKU23_camel_Ethiopia_CAC1019_2015_nsp3_VIPR_ALG4_QEY10622_1_10850_11710_1_2015_02_21_Ethiopia_Camel_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
12694_2012_nsp3_VIPR_ALG4_701216743_10857_11717_1_2012_05_China_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
R_AH187_nsp3_VIPR_ALG4_145208950_10842_11702_1_NA_USA_Cattle_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
BCOV_China_SWUN_A10_2018_nsp3_VIPR_ALG4_QOV05174_1_10858_11718_1_2018_11_01_China_Cattle_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
IWT_5_nsp3_VIPR_ALG4_BBM60984_1_10834_11694_1_2011_11_Japan_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
DB2_nsp3_VIPR_ALG4_331264482_10843_11703_1_1983_NA_Cattle_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
OC43_human_USA_873_19_1987_nsp3_VIPR_ALG4_530802412_10838_11698_1_1987_03_17_USA_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
IWT_20_nsp3_VIPR_ALG4_BBM61094_1_10834_11694_1_2016_12_Japan_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFRLLGIGGVPIIEVSQFQ
OC43_human_USA_9612_9_1996_nsp3_VIPR_ALG4_530802204_10838_11698_1_1996_12_04_USA_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
LY341_nsp3_VIPR_ALG4_721347196_10858_11718_1_2011_10_03_China_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
Kakegawa_nsp3_VIPR_ALG4_155369168_10858_11718_1_NA_Japan_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
19572_Belgium_2004_nsp3_VIPR_ALG4_62530899_10858_11718_1_NA_Belgium_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
TCG_26_nsp3_VIPR_ALG4_BBM61504_1_10831_11691_1_2017_12_Japan_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
GZYF_26_nsp3_VIPR_ALG4_AXX83330_1_10782_11642_1_2015_05_21_China_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
MDS16_nsp3_VIPR_ALG4_QBQ01836_1_10837_11697_1_NA_NA_Unknown_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
E_AH187_TC_nsp3_VIPR_ALG4_251748090_10842_11702_1_2000_01_01_USA_Cattle_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
BJ232_nsp3_VIPR_ALG4_AQT26494_1_10791_11651_1_2014_China_Dog_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
5445_2007_nsp3_VIPR_ALG4_701216785_10857_11717_1_2007_06_China_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
HCoV_OC43_Seattle_USA_SC2770_2015_nsp3_VIPR_ALG4_ARK08647_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
HCoV_OC43_Seattle_USA_SC0839_2019_nsp3_VIPR_ALG4_QEG03763_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
HCoV_OC43_Seattle_USA_SC2854_2015_nsp3_VIPR_ALG4_ARU07583_1_10823_11683_1_2015_USA_Human_Betacoronavirus_1 YKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
******************************:****************
>TCG_22_nsp3_VIPR_ALG4_BBM61464_1_10814_11674_1_2016_12_Japan_Unknown_Betacoronavirus_1 TCAAAGCGCACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAATAACTATTTGGTTGTGTACAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTATAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTCTCTTTTATAATGTTTGTTGGCCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGTTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTCTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTACAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >BJ_165_nsp3_VIPR_ALG4_AXX83312_1_10761_11621_1_2015_06_09_China_Unknown_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTAGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCCCAATTTCAA >YC_55_nsp3_VIPR_ALG4_AXX83348_1_10761_11621_1_2015_03_12_China_Unknown_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTAGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >HCoV_OC43_Seattle_USA_SC2481_2015_nsp3_VIPR_ALG4_ARU07564_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGTACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACACCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >5352_2007_nsp3_VIPR_ALG4_701216673_10857_11717_1_2007_05_China_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >OC43_human_USA_901_41_1990_nsp3_VIPR_ALG4_530802215_10838_11698_1_1990_01_17_USA_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTTAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACACTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTCTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTTTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGGTAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGCTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGCTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >DcCoV_HKU23_camel_Nigeria_NV1385_2016_nsp3_VIPR_ALG4_QEY10662_1_10856_11716_1_2016_01_24_Nigeria_Camel_Betacoronavirus_1 TCAAAGCGCACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACGTTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGCTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAACAACTATTTGATTGTGTACAAGCAGACGTTTAGGGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTATAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTCGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >HCoV_OC43_Seattle_USA_SC0810_2019_nsp3_VIPR_ALG4_QEG03753_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGTACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACACCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >HCoV_OC43_USA_TCNP_00204_2017_nsp3_VIPR_ALG4_ATN39869_1_10849_11709_1_2017_01_03_USA_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGTACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACACCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >DcCoV_HKU23_camel_Ethiopia_CAC1019_2015_nsp3_VIPR_ALG4_QEY10622_1_10850_11710_1_2015_02_21_Ethiopia_Camel_Betacoronavirus_1 TCAAAGCGCACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACGTTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGCTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAACAACTATTTGATTGTGTACAAGCAGACATTTAGGGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTTATTTATGGTATGTTATTGCTTATAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTGTGATTTCTGTTGTTTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAAGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCTTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >12694_2012_nsp3_VIPR_ALG4_701216743_10857_11717_1_2012_05_China_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTAGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCCCAATTTCAA >R_AH187_nsp3_VIPR_ALG4_145208950_10842_11702_1_NA_USA_Cattle_Betacoronavirus_1 TCAAAGCGTACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAACAACTATTTGGTTGTGTACAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTATAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTCTCTTTTATAATGTTTGTTGGCCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >BCOV_China_SWUN_A10_2018_nsp3_VIPR_ALG4_QOV05174_1_10858_11718_1_2018_11_01_China_Cattle_Betacoronavirus_1 TCAAAGCGTACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGACTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAACAACTATTTGGTTGTGTATAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTTATTTACGGCATGTTATTGCTTATAGGAATGGTTTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGCACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTTCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >IWT_5_nsp3_VIPR_ALG4_BBM60984_1_10834_11694_1_2011_11_Japan_Unknown_Betacoronavirus_1 TCAAAGCGCATTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACATTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAATAACTATTTGGTTGTGTACAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGATTATACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTACAGGAACGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTCTCTTTTATAATGTTTGTTGGCCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >DB2_nsp3_VIPR_ALG4_331264482_10843_11703_1_1983_NA_Cattle_Betacoronavirus_1 TCAAAGCGTACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAACAACTATTTGGTTGTGTACAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTATAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >OC43_human_USA_873_19_1987_nsp3_VIPR_ALG4_530802412_10838_11698_1_1987_03_17_USA_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTTAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACACTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTCTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTTTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGGTAGTGCTTTTGTGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGCTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGCTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >IWT_20_nsp3_VIPR_ALG4_BBM61094_1_10834_11694_1_2016_12_Japan_Unknown_Betacoronavirus_1 TCAAAGCGCACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTTCTGTATAATAACTATTTGGTTGTGTACAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTATAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTCTCTTTTATAATGTTTGTTGGCCGTGTGATTTCTGTTGTCTCTTTGTGGTATATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTCTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTACAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAGGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >OC43_human_USA_9612_9_1996_nsp3_VIPR_ALG4_530802204_10838_11698_1_1996_12_04_USA_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTCTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCTTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >LY341_nsp3_VIPR_ALG4_721347196_10858_11718_1_2011_10_03_China_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGTACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >Kakegawa_nsp3_VIPR_ALG4_155369168_10858_11718_1_NA_Japan_Unknown_Betacoronavirus_1 TCAAAGCGTACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAACAACTATTTGGTTGTGTACAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTAATTTATGGCATGTTATTGCTTATAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTCTCTTTTATAATGTTTGTTGGTCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >19572_Belgium_2004_nsp3_VIPR_ALG4_62530899_10858_11718_1_NA_Belgium_Unknown_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >TCG_26_nsp3_VIPR_ALG4_BBM61504_1_10831_11691_1_2017_12_Japan_Unknown_Betacoronavirus_1 TCAAAGCGCACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAACAATTATTTGGTTGTGTACAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTATAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTCTCTTTTATAATGTTTGTTGGCCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTCTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTACAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >GZYF_26_nsp3_VIPR_ALG4_AXX83330_1_10782_11642_1_2015_05_21_China_Unknown_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTAGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCCCAATTTCAA >MDS16_nsp3_VIPR_ALG4_QBQ01836_1_10837_11697_1_NA_NA_Unknown_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTAGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >E_AH187_TC_nsp3_VIPR_ALG4_251748090_10842_11702_1_2000_01_01_USA_Cattle_Betacoronavirus_1 TCAAAGCGTACTAGATTGGTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAACAACTATTTGGTTGTGTACAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTATAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTCTCTTTTATAATGTTTGTTGGCCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCTCTTTTTGGTACTTACACATGGACAACAGCTTTATCTATGGCTGCAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >BJ232_nsp3_VIPR_ALG4_AQT26494_1_10791_11651_1_2014_China_Dog_Betacoronavirus_1 TCAAAGCGTATTAGATTGTTTAAAGGCATTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGTATAATTACAGCATTTGTGAAATGGACTATGTTTATGTATGTAACTACTAATATGCTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAACATAAGCATCTTTATTTGACTATGTATATAATTCCTGTGCTTTTTACACTGCTGTATAACAACTATTTGGTTGTGTACAAGCAGACATTTAGAGGCTATGTTTATGCATGGCTATCATATTATGTTCCATCAGTTGAGTATACTTATACTGATGAAGTAATTTATGGCATGTTATTGCTTATAGGAATGGCTTTTGTTACATTACGTAGCATTAACCATGATTTGTTCTCTTTTATAATGTTTGTAGGTCGTGTGATTTCTGTTGTCTCTTTGTGGTACATGGGTTCTAACTTAGAAGAAGAAATTCTTCTTATGTTGGTTTCTCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTTTTGTATTTTACAGATATACCTCAAATTAAGATAGTGCTTGTATGCTATTTGTTTATAGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAGGCCCTTATGCTTAATTTTAAGCTTTTGGGTATTGGAGGTGTGCCAATTATTGAAGTATCTCAATTTCAA >5445_2007_nsp3_VIPR_ALG4_701216785_10857_11717_1_2007_06_China_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGCACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACTCCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >HCoV_OC43_Seattle_USA_SC2770_2015_nsp3_VIPR_ALG4_ARK08647_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGTACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACACCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >HCoV_OC43_Seattle_USA_SC0839_2019_nsp3_VIPR_ALG4_QEG03763_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGTACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACACCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA >HCoV_OC43_Seattle_USA_SC2854_2015_nsp3_VIPR_ALG4_ARU07583_1_10823_11683_1_2015_USA_Human_Betacoronavirus_1 TCAAAACGCACTAGATTGTTTAAAGGTACTGTTTGTTGGATTATGGCTTCTACATTTTTGTTTAGTTGCATAATTACAGCATTTGTGAAATGGACTATGTTCATGTATGTAACTACTAATATGTTTAGTATTACGTTTTGTGCACTTTGTGTTATAAGTTTGGCCATGTTGTTGGTTAAGCATAAGCATCTTTATTTGACTATGTATATAACACCTGTGCTTTTTACATTGTTGTATAACAACTATTTGGTTGTGTACAAGCATACATTTAGAGGCTATGTTTATGCATGGCTATCGTATTATGTTCCATCAGTTGAGTACACTTATACTGATGAAGTTATTTATGGCATGTTATTGCTTGTAGGAATGGTCTTTGTTACATTACGTAGCATTAACCATGATTTGTTTTCTTTTATAATGTTTGTTGGTCGTTTGATTTCTGTTTTCTCTTTGTGGTACAAGGGTTCTAACTTAGAGGAAGAAATTCTTCTTATGTTGGCTTCCCTTTTTGGTACTTACACATGGACAACAGTTTTATCTATGGCTGTAGCAAAGGTTATTGCTAAGTGGGTTGCTGTGAATGTCTTGTATTTCACAGATATACCTCAAATTAAGATAGTGCTTTTGTGCTATTTGTTTATTGGTTATATTATTAGCTGTTATTGGGGTTTGTTTTCCTTGATGAACAGTTTGTTTAGAATGCCTTTGGGTGTTTATAATTATAAAATTTCAGTACAGGAATTAAGATATATGAATGCTAATGGATTGCGCCCTCCTAAGAATAGTTTTGAAGCCCTTATGCTTAATTTTAAGCTGTTGGGTATTGGAGGTGTTCCAATCATTGAAGTATCTCAATTTCAA
>TCG_22_nsp3_VIPR_ALG4_BBM61464_1_10814_11674_1_2016_12_Japan_Unknown_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVVVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >BJ_165_nsp3_VIPR_ALG4_AXX83312_1_10761_11621_1_2015_06_09_China_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >YC_55_nsp3_VIPR_ALG4_AXX83348_1_10761_11621_1_2015_03_12_China_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >HCoV_OC43_Seattle_USA_SC2481_2015_nsp3_VIPR_ALG4_ARU07564_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >5352_2007_nsp3_VIPR_ALG4_701216673_10857_11717_1_2007_05_China_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >OC43_human_USA_901_41_1990_nsp3_VIPR_ALG4_530802215_10838_11698_1_1990_01_17_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKVVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >DcCoV_HKU23_camel_Nigeria_NV1385_2016_nsp3_VIPR_ALG4_QEY10662_1_10856_11716_1_2016_01_24_Nigeria_Camel_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLIVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >HCoV_OC43_Seattle_USA_SC0810_2019_nsp3_VIPR_ALG4_QEG03753_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >HCoV_OC43_USA_TCNP_00204_2017_nsp3_VIPR_ALG4_ATN39869_1_10849_11709_1_2017_01_03_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >DcCoV_HKU23_camel_Ethiopia_CAC1019_2015_nsp3_VIPR_ALG4_QEY10622_1_10850_11710_1_2015_02_21_Ethiopia_Camel_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLIVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >12694_2012_nsp3_VIPR_ALG4_701216743_10857_11717_1_2012_05_China_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >R_AH187_nsp3_VIPR_ALG4_145208950_10842_11702_1_NA_USA_Cattle_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >BCOV_China_SWUN_A10_2018_nsp3_VIPR_ALG4_QOV05174_1_10858_11718_1_2018_11_01_China_Cattle_Betacoronavirus_1 SKRTRLVKGIVCWIMTSTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >IWT_5_nsp3_VIPR_ALG4_BBM60984_1_10834_11694_1_2011_11_Japan_Unknown_Betacoronavirus_1 SKRIRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVDYTYTDEVIYGMLLLTGTVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >DB2_nsp3_VIPR_ALG4_331264482_10843_11703_1_1983_NA_Cattle_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >OC43_human_USA_873_19_1987_nsp3_VIPR_ALG4_530802412_10838_11698_1_1987_03_17_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKVVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >IWT_20_nsp3_VIPR_ALG4_BBM61094_1_10834_11694_1_2016_12_Japan_Unknown_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFRLLGIGGVPIIEVSQFQ >OC43_human_USA_9612_9_1996_nsp3_VIPR_ALG4_530802204_10838_11698_1_1996_12_04_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >LY341_nsp3_VIPR_ALG4_721347196_10858_11718_1_2011_10_03_China_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCVLCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >Kakegawa_nsp3_VIPR_ALG4_155369168_10858_11718_1_NA_Japan_Unknown_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >19572_Belgium_2004_nsp3_VIPR_ALG4_62530899_10858_11718_1_NA_Belgium_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >TCG_26_nsp3_VIPR_ALG4_BBM61504_1_10831_11691_1_2017_12_Japan_Unknown_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >GZYF_26_nsp3_VIPR_ALG4_AXX83330_1_10782_11642_1_2015_05_21_China_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >MDS16_nsp3_VIPR_ALG4_QBQ01836_1_10837_11697_1_NA_NA_Unknown_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >E_AH187_TC_nsp3_VIPR_ALG4_251748090_10842_11702_1_2000_01_01_USA_Cattle_Betacoronavirus_1 SKRTRLVKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMVFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLASLFGTYTWTTALSMAAAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >BJ232_nsp3_VIPR_ALG4_AQT26494_1_10791_11651_1_2014_China_Dog_Betacoronavirus_1 SKRIRLFKGIVCWIMASTFLFSCIITAFVKWTMFMYVTTNMLSITFCALCVISLAMLLVKHKHLYLTMYIIPVLFTLLYNNYLVVYKQTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLIGMAFVTLRSINHDLFSFIMFVGRVISVVSLWYMGSNLEEEILLMLVSLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLVCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >5445_2007_nsp3_VIPR_ALG4_701216785_10857_11717_1_2007_06_China_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >HCoV_OC43_Seattle_USA_SC2770_2015_nsp3_VIPR_ALG4_ARK08647_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >HCoV_OC43_Seattle_USA_SC0839_2019_nsp3_VIPR_ALG4_QEG03763_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ >HCoV_OC43_Seattle_USA_SC2854_2015_nsp3_VIPR_ALG4_ARU07583_1_10823_11683_1_2015_USA_Human_Betacoronavirus_1 SKRTRLFKGTVCWIMASTFLFSCIITAFVKWTMFMYVTTNMFSITFCALCVISLAMLLVKHKHLYLTMYITPVLFTLLYNNYLVVYKHTFRGYVYAWLSYYVPSVEYTYTDEVIYGMLLLVGMVFVTLRSINHDLFSFIMFVGRLISVFSLWYKGSNLEEEILLMLASLFGTYTWTTVLSMAVAKVIAKWVAVNVLYFTDIPQIKIVLLCYLFIGYIISCYWGLFSLMNSLFRMPLGVYNYKISVQELRYMNANGLRPPKNSFEALMLNFKLLGIGGVPIIEVSQFQ
Reading sequence file /data//pss_subsets/DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result/original_alignment/codeml/fasta/DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result.1
Found 30 sequences of length 861
Alignment looks like a valid DNA alignment.
Estimated diversity is (pairwise deletion - ignoring missing/ambig): 2.3%
Found 50 informative sites.
Writing alignment of informative sites to: Phi.inf.sites
Writing list of informative sites to: Phi.inf.list
Calculating all pairwise incompatibilities...
Done: 0.0%100.0%
Using a window size of 80 with k as 5
Calculating analytical mean and variance
Doing permutation test for PHI
Doing permutation test for NSS
Doing Permutation test for MAXCHI
Writing alignment of polymorphic unambig sites to: Phi.poly.sites
Window size is 51 polymorphic sites
**p-Value(s)**
----------
NSS: 1.49e-01 (1000 permutations)
Max Chi^2: 2.88e-01 (1000 permutations)
PHI (Permutation): 9.46e-01 (1000 permutations)
PHI (Normal): 9.23e-01
#NEXUS
[ID: 8957953449]
begin taxa;
dimensions ntax=30;
taxlabels
R_AH187_nsp3_VIPR_ALG4_145208950_10842_11702_1_NA_USA_Cattle_Betacoronavirus_1
12694_2012_nsp3_VIPR_ALG4_701216743_10857_11717_1_2012_05_China_Human_Betacoronavirus_1
BCOV_China_SWUN_A10_2018_nsp3_VIPR_ALG4_QOV05174_1_10858_11718_1_2018_11_01_China_Cattle_Betacoronavirus_1
IWT_20_nsp3_VIPR_ALG4_BBM61094_1_10834_11694_1_2016_12_Japan_Unknown_Betacoronavirus_1
OC43_human_USA_873_19_1987_nsp3_VIPR_ALG4_530802412_10838_11698_1_1987_03_17_USA_Human_Betacoronavirus_1
OC43_human_USA_9612_9_1996_nsp3_VIPR_ALG4_530802204_10838_11698_1_1996_12_04_USA_Human_Betacoronavirus_1
TCG_26_nsp3_VIPR_ALG4_BBM61504_1_10831_11691_1_2017_12_Japan_Unknown_Betacoronavirus_1
19572_Belgium_2004_nsp3_VIPR_ALG4_62530899_10858_11718_1_NA_Belgium_Unknown_Betacoronavirus_1
5445_2007_nsp3_VIPR_ALG4_701216785_10857_11717_1_2007_06_China_Human_Betacoronavirus_1
BJ232_nsp3_VIPR_ALG4_AQT26494_1_10791_11651_1_2014_China_Dog_Betacoronavirus_1
HCoV_OC43_Seattle_USA_SC2481_2015_nsp3_VIPR_ALG4_ARU07564_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1
HCoV_OC43_Seattle_USA_SC2854_2015_nsp3_VIPR_ALG4_ARU07583_1_10823_11683_1_2015_USA_Human_Betacoronavirus_1
HCoV_OC43_Seattle_USA_SC0810_2019_nsp3_VIPR_ALG4_QEG03753_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1
TCG_22_nsp3_VIPR_ALG4_BBM61464_1_10814_11674_1_2016_12_Japan_Unknown_Betacoronavirus_1
YC_55_nsp3_VIPR_ALG4_AXX83348_1_10761_11621_1_2015_03_12_China_Unknown_Betacoronavirus_1
BJ_165_nsp3_VIPR_ALG4_AXX83312_1_10761_11621_1_2015_06_09_China_Unknown_Betacoronavirus_1
OC43_human_USA_901_41_1990_nsp3_VIPR_ALG4_530802215_10838_11698_1_1990_01_17_USA_Human_Betacoronavirus_1
5352_2007_nsp3_VIPR_ALG4_701216673_10857_11717_1_2007_05_China_Human_Betacoronavirus_1
DcCoV_HKU23_camel_Nigeria_NV1385_2016_nsp3_VIPR_ALG4_QEY10662_1_10856_11716_1_2016_01_24_Nigeria_Camel_Betacoronavirus_1
DcCoV_HKU23_camel_Ethiopia_CAC1019_2015_nsp3_VIPR_ALG4_QEY10622_1_10850_11710_1_2015_02_21_Ethiopia_Camel_Betacoronavirus_1
IWT_5_nsp3_VIPR_ALG4_BBM60984_1_10834_11694_1_2011_11_Japan_Unknown_Betacoronavirus_1
DB2_nsp3_VIPR_ALG4_331264482_10843_11703_1_1983_NA_Cattle_Betacoronavirus_1
Kakegawa_nsp3_VIPR_ALG4_155369168_10858_11718_1_NA_Japan_Unknown_Betacoronavirus_1
LY341_nsp3_VIPR_ALG4_721347196_10858_11718_1_2011_10_03_China_Human_Betacoronavirus_1
E_AH187_TC_nsp3_VIPR_ALG4_251748090_10842_11702_1_2000_01_01_USA_Cattle_Betacoronavirus_1
GZYF_26_nsp3_VIPR_ALG4_AXX83330_1_10782_11642_1_2015_05_21_China_Unknown_Betacoronavirus_1
MDS16_nsp3_VIPR_ALG4_QBQ01836_1_10837_11697_1_NA_NA_Unknown_Betacoronavirus_1
HCoV_OC43_USA_TCNP_00204_2017_nsp3_VIPR_ALG4_ATN39869_1_10849_11709_1_2017_01_03_USA_Human_Betacoronavirus_1
HCoV_OC43_Seattle_USA_SC0839_2019_nsp3_VIPR_ALG4_QEG03763_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1
HCoV_OC43_Seattle_USA_SC2770_2015_nsp3_VIPR_ALG4_ARK08647_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1
;
end;
begin trees;
translate
1 R_AH187_nsp3_VIPR_ALG4_145208950_10842_11702_1_NA_USA_Cattle_Betacoronavirus_1,
2 12694_2012_nsp3_VIPR_ALG4_701216743_10857_11717_1_2012_05_China_Human_Betacoronavirus_1,
3 BCOV_China_SWUN_A10_2018_nsp3_VIPR_ALG4_QOV05174_1_10858_11718_1_2018_11_01_China_Cattle_Betacoronavirus_1,
4 IWT_20_nsp3_VIPR_ALG4_BBM61094_1_10834_11694_1_2016_12_Japan_Unknown_Betacoronavirus_1,
5 OC43_human_USA_873_19_1987_nsp3_VIPR_ALG4_530802412_10838_11698_1_1987_03_17_USA_Human_Betacoronavirus_1,
6 OC43_human_USA_9612_9_1996_nsp3_VIPR_ALG4_530802204_10838_11698_1_1996_12_04_USA_Human_Betacoronavirus_1,
7 TCG_26_nsp3_VIPR_ALG4_BBM61504_1_10831_11691_1_2017_12_Japan_Unknown_Betacoronavirus_1,
8 19572_Belgium_2004_nsp3_VIPR_ALG4_62530899_10858_11718_1_NA_Belgium_Unknown_Betacoronavirus_1,
9 5445_2007_nsp3_VIPR_ALG4_701216785_10857_11717_1_2007_06_China_Human_Betacoronavirus_1,
10 BJ232_nsp3_VIPR_ALG4_AQT26494_1_10791_11651_1_2014_China_Dog_Betacoronavirus_1,
11 HCoV_OC43_Seattle_USA_SC2481_2015_nsp3_VIPR_ALG4_ARU07564_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1,
12 HCoV_OC43_Seattle_USA_SC2854_2015_nsp3_VIPR_ALG4_ARU07583_1_10823_11683_1_2015_USA_Human_Betacoronavirus_1,
13 HCoV_OC43_Seattle_USA_SC0810_2019_nsp3_VIPR_ALG4_QEG03753_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1,
14 TCG_22_nsp3_VIPR_ALG4_BBM61464_1_10814_11674_1_2016_12_Japan_Unknown_Betacoronavirus_1,
15 YC_55_nsp3_VIPR_ALG4_AXX83348_1_10761_11621_1_2015_03_12_China_Unknown_Betacoronavirus_1,
16 BJ_165_nsp3_VIPR_ALG4_AXX83312_1_10761_11621_1_2015_06_09_China_Unknown_Betacoronavirus_1,
17 OC43_human_USA_901_41_1990_nsp3_VIPR_ALG4_530802215_10838_11698_1_1990_01_17_USA_Human_Betacoronavirus_1,
18 5352_2007_nsp3_VIPR_ALG4_701216673_10857_11717_1_2007_05_China_Human_Betacoronavirus_1,
19 DcCoV_HKU23_camel_Nigeria_NV1385_2016_nsp3_VIPR_ALG4_QEY10662_1_10856_11716_1_2016_01_24_Nigeria_Camel_Betacoronavirus_1,
20 DcCoV_HKU23_camel_Ethiopia_CAC1019_2015_nsp3_VIPR_ALG4_QEY10622_1_10850_11710_1_2015_02_21_Ethiopia_Camel_Betacoronavirus_1,
21 IWT_5_nsp3_VIPR_ALG4_BBM60984_1_10834_11694_1_2011_11_Japan_Unknown_Betacoronavirus_1,
22 DB2_nsp3_VIPR_ALG4_331264482_10843_11703_1_1983_NA_Cattle_Betacoronavirus_1,
23 Kakegawa_nsp3_VIPR_ALG4_155369168_10858_11718_1_NA_Japan_Unknown_Betacoronavirus_1,
24 LY341_nsp3_VIPR_ALG4_721347196_10858_11718_1_2011_10_03_China_Human_Betacoronavirus_1,
25 E_AH187_TC_nsp3_VIPR_ALG4_251748090_10842_11702_1_2000_01_01_USA_Cattle_Betacoronavirus_1,
26 GZYF_26_nsp3_VIPR_ALG4_AXX83330_1_10782_11642_1_2015_05_21_China_Unknown_Betacoronavirus_1,
27 MDS16_nsp3_VIPR_ALG4_QBQ01836_1_10837_11697_1_NA_NA_Unknown_Betacoronavirus_1,
28 HCoV_OC43_USA_TCNP_00204_2017_nsp3_VIPR_ALG4_ATN39869_1_10849_11709_1_2017_01_03_USA_Human_Betacoronavirus_1,
29 HCoV_OC43_Seattle_USA_SC0839_2019_nsp3_VIPR_ALG4_QEG03763_1_10854_11714_1_2019_USA_Human_Betacoronavirus_1,
30 HCoV_OC43_Seattle_USA_SC2770_2015_nsp3_VIPR_ALG4_ARK08647_1_10819_11679_1_2015_USA_Human_Betacoronavirus_1
;
[Note: This tree contains information on the topology,
branch lengths (if present), and the probability
of the partition indicated by the branch.]
tree con_50_majrule = (1:5.423437e-04,25:5.592208e-04,(((4:3.051245e-03,14:1.381882e-03)0.707:1.123095e-03,7:1.496651e-03)0.891:2.194403e-03,21:5.295345e-03)0.873:1.691429e-03,((((((((2:5.337130e-04,16:5.542711e-04,26:5.645664e-04)0.973:1.333984e-03,15:5.794369e-04,27:5.874997e-04)0.987:1.346147e-03,8:5.348919e-04,9:5.275726e-04,(11:5.795564e-04,12:5.518312e-04,13:5.690121e-04,28:5.518758e-04,29:5.752397e-04,30:5.444793e-04)1.000:2.144596e-03,18:5.419383e-04,24:2.155761e-03)0.905:1.385718e-03,6:2.258860e-03)0.964:3.041456e-03,(5:1.184960e-03,17:6.641296e-04)1.000:5.468260e-03)1.000:2.067492e-02,(19:2.078846e-03,20:3.751233e-03)1.000:4.089492e-03)0.587:1.267227e-03,3:5.461833e-03,22:6.040931e-04)0.872:1.392282e-03,(10:9.707699e-03,23:5.480548e-04)0.993:1.452092e-03)0.856:1.377553e-03);
[Note: This tree contains information only on the topology
and branch lengths (median of the posterior probability density).]
tree con_50_majrule = (1:5.423437e-04,25:5.592208e-04,(((4:3.051245e-03,14:1.381882e-03):1.123095e-03,7:1.496651e-03):2.194403e-03,21:5.295345e-03):1.691429e-03,((((((((2:5.337130e-04,16:5.542711e-04,26:5.645664e-04):1.333984e-03,15:5.794369e-04,27:5.874997e-04):1.346147e-03,8:5.348919e-04,9:5.275726e-04,(11:5.795564e-04,12:5.518312e-04,13:5.690121e-04,28:5.518758e-04,29:5.752397e-04,30:5.444793e-04):2.144596e-03,18:5.419383e-04,24:2.155761e-03):1.385718e-03,6:2.258860e-03):3.041456e-03,(5:1.184960e-03,17:6.641296e-04):5.468260e-03):2.067492e-02,(19:2.078846e-03,20:3.751233e-03):4.089492e-03):1.267227e-03,3:5.461833e-03,22:6.040931e-04):1.392282e-03,(10:9.707699e-03,23:5.480548e-04):1.452092e-03):1.377553e-03);
end;
Estimated marginal likelihoods for runs sampled in files
"/data/mrbayes_input.nex.run1.p" and "/data/mrbayes_input.nex.run2.p":
(Use the harmonic mean for Bayes factor comparisons of models)
(Values are saved to the file /data/mrbayes_input.nex.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1688.12 -1715.08
2 -1689.58 -1718.83
--------------------------------------
TOTAL -1688.60 -1718.16
--------------------------------------
Model parameter summaries over the runs sampled in files
"/data/mrbayes_input.nex.run1.p" and "/data/mrbayes_input.nex.run2.p":
Summaries are based on a total of 3002 samples from 2 runs.
Each run produced 2001 samples of which 1501 samples were included.
Parameter summaries saved to file "/data/mrbayes_input.nex.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.120030 0.000253 0.088427 0.149303 0.119003 1024.47 1189.67 1.000
r(A<->C){all} 0.018073 0.000301 0.000003 0.052427 0.013106 487.71 534.06 1.000
r(A<->G){all} 0.204244 0.002232 0.117116 0.297482 0.200120 534.16 578.09 1.000
r(A<->T){all} 0.038181 0.000219 0.012680 0.067539 0.036179 827.33 902.96 1.003
r(C<->G){all} 0.023248 0.000544 0.000005 0.069301 0.016036 582.42 638.27 1.003
r(C<->T){all} 0.628434 0.003234 0.517576 0.734594 0.630819 589.07 625.89 1.001
r(G<->T){all} 0.087819 0.000650 0.038621 0.135669 0.085568 772.95 830.22 1.000
pi(A){all} 0.251390 0.000203 0.222291 0.277740 0.251077 1152.82 1166.98 1.000
pi(C){all} 0.124868 0.000115 0.104527 0.145533 0.124464 1033.74 1089.21 1.000
pi(G){all} 0.197673 0.000169 0.174426 0.224119 0.197007 1118.39 1205.53 1.000
pi(T){all} 0.426070 0.000256 0.396225 0.458055 0.426005 1025.29 1138.20 1.001
alpha{1,2} 0.178722 0.062543 0.000047 0.530809 0.110128 1077.44 1123.65 1.000
alpha{3} 2.055394 1.394859 0.315402 4.359189 1.829020 1174.67 1177.48 1.000
pinvar{all} 0.230526 0.018712 0.000432 0.470827 0.220687 1031.33 1112.79 1.000
------------------------------------------------------------------------------------------------------
* Convergence diagnostic (ESS = Estimated Sample Size); min and avg values
correspond to minimal and average ESS among runs.
ESS value below 100 may indicate that the parameter is undersampled.
+ Convergence diagnostic (PSRF = Potential Scale Reduction Factor; Gelman
and Rubin, 1992) should approach 1.0 as runs converge.
CODONML (in paml version 4.9h, March 2018) /data/fasta_checked/DcCoV_HKU23_camel_Morocco_CAC2586_2016_nsp3_VIPR_ALG4_QEY10630_1_10848_11708_1_2016_03_05_Morocco_Camel_Betacoronavirus_1.result.1
Model: One dN/dS ratio,
Codon frequency model: F3x4
Site-class models:
ns = 30 ls = 287
Codon usage in sequences
--------------------------------------------------------------------------------------------------------------------------------------
Phe TTT 16 19 19 19 19 19 | Ser TCT 8 6 7 7 7 7 | Tyr TAT 18 18 18 18 18 18 | Cys TGT 5 4 4 4 4 4
TTC 3 3 3 3 3 2 | TCC 1 3 2 2 2 2 | TAC 4 4 4 4 4 4 | TGC 1 2 2 2 2 2
Leu TTA 5 6 6 5 5 5 | TCA 4 3 3 3 3 4 | *** TAA 0 0 0 0 0 0 | *** TGA 0 0 0 0 0 0
TTG 19 22 22 23 23 21 | TCG 0 1 1 1 1 0 | TAG 0 0 0 0 0 0 | Trp TGG 7 7 7 7 7 7
--------------------------------------------------------------------------------------------------------------------------------------
Leu CTT 12 10 10 10 10 11 | Pro CCT 5 5 5 5 5 5 | His CAT 3 4 4 4 4 4 | Arg CGT 2 2 2 2 2 2
CTC 0 0 0 0 0 0 | CCC 0 0 0 0 0 0 | CAC 0 0 0 0 0 0 | CGC 2 2 2 2 2 2
CTA 1 1 1 1 1 1 | CCA 2 2 2 2 2 2 | Gln CAA 3 3 3 3 3 3 | CGA 0 0 0 0 0 0
CTG 2 1 1 1 1 3 | CCG 0 0 0 0 0 0 | CAG 2 1 1 1 1 1 | CGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Ile ATT 17 15 15 15 15 15 | Thr ACT 8 10 10 9 10 10 | Asn AAT 8 7 7 7 7 7 | Ser AGT 5 5 5 5 5 5
ATC 0 1 1 1 1 1 | ACC 0 0 0 0 0 0 | AAC 4 5 5 5 5 5 | AGC 2 2 2 2 2 2
ATA 8 6 6 6 6 5 | ACA 9 9 9 10 9 9 | Lys AAA 4 4 4 4 4 4 | Arg AGA 4 4 4 4 4 4
Met ATG 16 15 15 15 15 15 | ACG 1 1 1 1 1 1 | AAG 8 9 9 9 9 9 | AGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Val GTT 17 16 16 16 16 17 | Ala GCT 6 6 6 6 6 6 | Asp GAT 3 3 3 3 3 3 | Gly GGT 7 8 8 9 8 7
GTC 2 2 2 2 2 2 | GCC 2 2 2 2 2 2 | GAC 0 0 0 0 0 0 | GGC 4 3 3 2 3 4
GTA 4 5 5 5 5 6 | GCA 5 4 4 4 4 4 | Glu GAA 6 6 6 6 6 6 | GGA 3 3 3 3 3 3
GTG 7 5 5 5 5 4 | GCG 0 0 0 0 0 0 | GAG 2 2 2 2 2 2 | GGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
--------------------------------------------------------------------------------------------------------------------------------------
Phe TTT 17 19 19 18 19 17 | Ser TCT 8 7 7 9 6 8 | Tyr TAT 19 18 18 19 18 19 | Cys TGT 5 4 4 5 4 5
TTC 2 3 3 1 3 2 | TCC 1 2 2 0 3 1 | TAC 3 4 4 3 4 3 | TGC 1 2 2 1 2 1
Leu TTA 5 5 5 5 6 5 | TCA 4 3 3 4 3 4 | *** TAA 0 0 0 0 0 0 | *** TGA 0 0 0 0 0 0
TTG 18 23 23 18 22 19 | TCG 0 1 1 0 1 0 | TAG 0 0 0 0 0 0 | Trp TGG 7 7 7 7 7 7
--------------------------------------------------------------------------------------------------------------------------------------
Leu CTT 12 10 10 12 10 12 | Pro CCT 5 5 5 5 5 5 | His CAT 3 4 4 3 4 3 | Arg CGT 2 2 2 2 2 3
CTC 0 0 0 0 0 0 | CCC 0 0 0 0 0 0 | CAC 0 0 0 0 0 0 | CGC 2 2 2 2 2 1
CTA 1 1 1 1 1 1 | CCA 2 2 2 2 2 2 | Gln CAA 3 3 3 3 3 3 | CGA 0 0 0 0 0 0
CTG 3 1 1 3 1 2 | CCG 0 0 0 0 0 0 | CAG 2 1 1 2 1 2 | CGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Ile ATT 18 15 15 18 15 17 | Thr ACT 8 9 9 8 10 8 | Asn AAT 7 7 7 7 7 7 | Ser AGT 5 5 5 5 5 5
ATC 0 1 1 0 1 0 | ACC 0 0 0 0 0 0 | AAC 5 5 5 5 5 5 | AGC 2 2 2 2 2 2
ATA 8 6 6 8 6 8 | ACA 7 10 10 8 9 9 | Lys AAA 4 4 4 5 4 4 | Arg AGA 3 4 4 3 4 4
Met ATG 16 15 15 16 15 16 | ACG 3 1 1 2 1 1 | AAG 8 9 9 7 9 8 | AGG 1 0 0 1 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Val GTT 15 16 16 16 16 16 | Ala GCT 7 6 6 7 6 7 | Asp GAT 3 3 3 3 3 3 | Gly GGT 8 9 9 9 8 7
GTC 2 2 2 1 2 2 | GCC 2 2 2 2 2 2 | GAC 0 0 0 0 0 0 | GGC 3 2 2 2 3 4
GTA 4 5 5 4 5 4 | GCA 5 4 4 5 4 5 | Glu GAA 6 6 6 6 6 6 | GGA 3 3 3 3 3 3
GTG 7 5 5 7 5 7 | GCG 0 0 0 0 0 0 | GAG 2 2 2 2 2 2 | GGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
--------------------------------------------------------------------------------------------------------------------------------------
Phe TTT 18 17 18 19 16 19 | Ser TCT 8 8 8 7 8 8 | Tyr TAT 19 19 19 18 19 18 | Cys TGT 5 5 5 4 5 4
TTC 1 2 1 2 3 3 | TCC 1 1 1 2 1 1 | TAC 3 3 3 4 3 4 | TGC 1 1 1 2 1 2
Leu TTA 5 5 5 5 5 5 | TCA 4 4 4 4 4 4 | *** TAA 0 0 0 0 0 0 | *** TGA 0 0 0 0 0 0
TTG 19 19 19 21 19 23 | TCG 0 0 0 0 0 0 | TAG 0 0 0 0 0 0 | Trp TGG 7 7 7 7 7 7
--------------------------------------------------------------------------------------------------------------------------------------
Leu CTT 12 12 12 11 13 9 | Pro CCT 5 5 5 5 5 5 | His CAT 3 3 3 4 3 4 | Arg CGT 3 2 3 2 2 2
CTC 0 0 0 0 0 1 | CCC 0 0 0 0 0 0 | CAC 0 0 0 0 0 0 | CGC 1 2 1 2 2 2
CTA 1 1 1 1 1 1 | CCA 2 2 2 2 2 2 | Gln CAA 3 3 3 3 3 3 | CGA 0 0 0 0 0 0
CTG 2 2 2 3 1 1 | CCG 0 0 0 0 0 0 | CAG 2 2 2 1 2 1 | CGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Ile ATT 17 18 17 14 17 15 | Thr ACT 9 7 8 10 8 10 | Asn AAT 7 8 7 7 8 7 | Ser AGT 5 5 5 5 5 5
ATC 0 0 0 1 0 1 | ACC 0 0 0 0 0 0 | AAC 5 4 5 5 4 5 | AGC 2 2 2 2 2 2
ATA 8 7 8 6 8 6 | ACA 9 11 9 9 9 9 | Lys AAA 4 4 4 4 4 4 | Arg AGA 4 4 4 4 4 4
Met ATG 16 15 16 15 16 15 | ACG 1 1 1 1 1 1 | AAG 8 8 8 9 7 9 | AGG 0 0 0 0 1 0
--------------------------------------------------------------------------------------------------------------------------------------
Val GTT 18 16 16 17 16 16 | Ala GCT 6 7 7 6 7 6 | Asp GAT 3 4 3 3 3 3 | Gly GGT 7 7 8 7 7 8
GTC 1 2 2 2 2 2 | GCC 2 2 2 2 2 2 | GAC 0 0 0 0 0 0 | GGC 4 4 3 4 4 3
GTA 4 4 4 6 4 5 | GCA 5 5 5 4 5 4 | Glu GAA 6 6 6 6 6 6 | GGA 3 3 3 3 3 3
GTG 6 7 7 4 7 5 | GCG 0 0 0 0 0 0 | GAG 2 1 2 2 2 2 | GGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
--------------------------------------------------------------------------------------------------------------------------------------
Phe TTT 19 17 19 16 19 19 | Ser TCT 7 8 7 8 6 7 | Tyr TAT 18 19 18 18 18 18 | Cys TGT 4 5 4 5 4 4
TTC 3 2 3 3 3 3 | TCC 2 1 2 1 3 2 | TAC 4 3 4 4 4 4 | TGC 2 1 2 1 2 2
Leu TTA 5 5 5 5 6 6 | TCA 3 4 3 4 3 3 | *** TAA 0 0 0 0 0 0 | *** TGA 0 0 0 0 0 0
TTG 23 19 23 19 22 22 | TCG 1 0 1 0 1 1 | TAG 0 0 0 0 0 0 | Trp TGG 7 7 7 7 7 7
--------------------------------------------------------------------------------------------------------------------------------------
Leu CTT 10 12 10 12 10 10 | Pro CCT 5 5 5 5 5 5 | His CAT 4 3 4 3 4 4 | Arg CGT 2 3 2 2 2 2
CTC 0 0 0 0 0 0 | CCC 0 0 0 0 0 0 | CAC 0 0 0 0 0 0 | CGC 2 1 2 2 2 2
CTA 1 1 1 1 1 1 | CCA 2 2 2 2 2 2 | Gln CAA 3 3 3 3 3 3 | CGA 0 0 0 0 0 0
CTG 1 2 1 2 1 1 | CCG 0 0 0 0 0 0 | CAG 1 2 1 2 1 1 | CGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Ile ATT 16 17 15 17 15 15 | Thr ACT 9 8 10 8 10 10 | Asn AAT 7 7 7 8 7 7 | Ser AGT 5 5 5 5 5 5
ATC 1 0 1 0 1 1 | ACC 0 0 0 0 0 0 | AAC 5 5 5 4 5 5 | AGC 2 2 2 2 2 2
ATA 6 8 6 8 6 6 | ACA 9 9 9 9 9 9 | Lys AAA 4 4 4 4 4 4 | Arg AGA 4 4 4 4 4 4
Met ATG 15 16 15 16 15 15 | ACG 1 1 1 1 1 1 | AAG 9 8 9 8 9 9 | AGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Val GTT 16 15 16 16 16 16 | Ala GCT 6 7 6 7 6 6 | Asp GAT 3 3 3 3 3 3 | Gly GGT 8 8 8 7 8 8
GTC 2 2 2 2 2 2 | GCC 2 2 2 2 2 2 | GAC 0 0 0 0 0 0 | GGC 3 3 3 4 3 3
GTA 6 5 5 4 5 5 | GCA 3 5 4 5 4 4 | Glu GAA 6 6 6 6 6 6 | GGA 3 3 3 3 3 3
GTG 5 7 5 7 5 5 | GCG 0 0 0 0 0 0 | GAG 2 2 2 2 2 2 | GGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
--------------------------------------------------------------------------------------------------------------------------------------
Phe TTT 17 19 19 19 19 19 | Ser TCT 8 8 7 7 7 7 | Tyr TAT 19 19 18 18 18 18 | Cys TGT 5 5 4 4 4 4
TTC 2 1 3 3 3 3 | TCC 1 1 2 2 2 2 | TAC 3 3 4 4 4 4 | TGC 1 1 2 2 2 2
Leu TTA 5 5 5 5 5 5 | TCA 4 4 3 3 3 3 | *** TAA 0 0 0 0 0 0 | *** TGA 0 0 0 0 0 0
TTG 19 19 23 23 23 23 | TCG 0 0 1 1 1 1 | TAG 0 0 0 0 0 0 | Trp TGG 7 7 7 7 7 7
--------------------------------------------------------------------------------------------------------------------------------------
Leu CTT 12 12 10 10 10 10 | Pro CCT 5 5 5 5 5 5 | His CAT 3 3 4 4 4 4 | Arg CGT 3 3 2 2 2 2
CTC 0 0 0 0 0 0 | CCC 0 0 0 0 0 0 | CAC 0 0 0 0 0 0 | CGC 1 1 2 2 2 2
CTA 1 1 1 1 1 1 | CCA 2 2 2 2 2 2 | Gln CAA 3 3 3 3 3 3 | CGA 0 0 0 0 0 0
CTG 2 2 1 1 1 1 | CCG 0 0 0 0 0 0 | CAG 2 2 1 1 1 1 | CGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Ile ATT 17 18 15 15 15 15 | Thr ACT 8 7 10 9 9 9 | Asn AAT 7 7 7 7 7 7 | Ser AGT 5 5 5 5 5 5
ATC 0 0 1 1 1 1 | ACC 0 0 0 0 0 0 | AAC 5 5 5 5 5 5 | AGC 2 2 2 2 2 2
ATA 8 8 6 6 6 6 | ACA 9 9 9 10 10 10 | Lys AAA 4 4 4 4 4 4 | Arg AGA 4 4 4 4 4 4
Met ATG 16 16 15 15 15 15 | ACG 1 1 1 1 1 1 | AAG 8 8 9 9 9 9 | AGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Val GTT 16 15 16 16 16 16 | Ala GCT 7 6 6 6 6 6 | Asp GAT 3 3 3 3 3 3 | Gly GGT 7 8 8 9 9 9
GTC 2 1 2 2 2 2 | GCC 2 2 2 2 2 2 | GAC 0 0 0 0 0 0 | GGC 4 3 3 2 2 2
GTA 4 7 5 5 5 5 | GCA 5 4 4 4 4 4 | Glu GAA 6 6 6 6 6 6 | GGA 3 3 3 3 3 3
GTG 7 7 5 5 5 5 | GCG 0 0 0 0 0 0 | GAG 2 2 2 2 2 2 | GGG 0 0 0 0 0 0
--------------------------------------------------------------------------------------------------------------------------------------
Codon position x base (3x4) table for each sequence.
#1: C238
position 1: T:0.31707 C:0.11847 A:0.32753 G:0.23693
position 2: T:0.44948 C:0.17770 A:0.22648 G:0.14634
position 3: T:0.48780 C:0.08711 A:0.20209 G:0.22300
Average T:0.41812 C:0.12776 A:0.25203 G:0.20209
#2: C60
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48084 C:0.10105 A:0.19512 G:0.22300
Average T:0.42160 C:0.13008 A:0.24971 G:0.19861
#3: C281
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09756 A:0.19512 G:0.22300
Average T:0.42276 C:0.12892 A:0.24971 G:0.19861
#4: C82
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09408 A:0.19512 G:0.22648
Average T:0.42276 C:0.12776 A:0.24971 G:0.19977
#5: C32
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09756 A:0.19164 G:0.22648
Average T:0.42276 C:0.12892 A:0.24855 G:0.19977
#6: C178
position 1: T:0.33101 C:0.11847 A:0.32056 G:0.22997
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48780 C:0.09756 A:0.19512 G:0.21951
Average T:0.42044 C:0.13240 A:0.24855 G:0.19861
#7: C71
position 1: T:0.31359 C:0.12195 A:0.33101 G:0.23345
position 2: T:0.44599 C:0.18118 A:0.22648 G:0.14634
position 3: T:0.49477 C:0.08014 A:0.19164 G:0.23345
Average T:0.41812 C:0.12776 A:0.24971 G:0.20441
#8: C78
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09408 A:0.19512 G:0.22648
Average T:0.42276 C:0.12776 A:0.24971 G:0.19977
#9: C93
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09408 A:0.19512 G:0.22648
Average T:0.42276 C:0.12776 A:0.24971 G:0.19977
#10: C66
position 1: T:0.31359 C:0.12195 A:0.33101 G:0.23345
position 2: T:0.44599 C:0.18118 A:0.22648 G:0.14634
position 3: T:0.50871 C:0.06620 A:0.19861 G:0.22648
Average T:0.42276 C:0.12311 A:0.25203 G:0.20209
#11: C7
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48084 C:0.10105 A:0.19512 G:0.22300
Average T:0.42160 C:0.13008 A:0.24971 G:0.19861
#12: C216
position 1: T:0.31707 C:0.11847 A:0.32753 G:0.23693
position 2: T:0.44599 C:0.18118 A:0.22648 G:0.14634
position 3: T:0.49477 C:0.08014 A:0.20209 G:0.22300
Average T:0.41928 C:0.12660 A:0.25203 G:0.20209
#13: C53
position 1: T:0.31707 C:0.11847 A:0.33101 G:0.23345
position 2: T:0.44599 C:0.18118 A:0.22648 G:0.14634
position 3: T:0.50523 C:0.07317 A:0.20209 G:0.21951
Average T:0.42276 C:0.12427 A:0.25319 G:0.19977
#14: C124
position 1: T:0.31707 C:0.11847 A:0.32753 G:0.23693
position 2: T:0.44251 C:0.18467 A:0.22648 G:0.14634
position 3: T:0.49826 C:0.08014 A:0.20557 G:0.21603
Average T:0.41928 C:0.12776 A:0.25319 G:0.19977
#15: C65
position 1: T:0.31707 C:0.11847 A:0.32753 G:0.23693
position 2: T:0.44599 C:0.18118 A:0.22648 G:0.14634
position 3: T:0.50174 C:0.07317 A:0.20209 G:0.22300
Average T:0.42160 C:0.12427 A:0.25203 G:0.20209
#16: C173
position 1: T:0.33101 C:0.11847 A:0.32056 G:0.22997
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09756 A:0.19861 G:0.21951
Average T:0.41928 C:0.13240 A:0.24971 G:0.19861
#17: C113
position 1: T:0.31707 C:0.11847 A:0.32753 G:0.23693
position 2: T:0.44599 C:0.18118 A:0.22300 G:0.14983
position 3: T:0.49477 C:0.08362 A:0.20209 G:0.21951
Average T:0.41928 C:0.12776 A:0.25087 G:0.20209
#18: C197
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09756 A:0.19512 G:0.22300
Average T:0.42276 C:0.12892 A:0.24971 G:0.19861
#19: C131
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44948 C:0.17422 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09756 A:0.19164 G:0.22648
Average T:0.42509 C:0.12660 A:0.24855 G:0.19977
#20: C130
position 1: T:0.31707 C:0.11847 A:0.32753 G:0.23693
position 2: T:0.44599 C:0.18118 A:0.22648 G:0.14634
position 3: T:0.49477 C:0.07666 A:0.20557 G:0.22300
Average T:0.41928 C:0.12544 A:0.25319 G:0.20209
#21: C11
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09756 A:0.19164 G:0.22648
Average T:0.42276 C:0.12892 A:0.24855 G:0.19977
#22: C242
position 1: T:0.31707 C:0.11847 A:0.32753 G:0.23693
position 2: T:0.44599 C:0.18118 A:0.22648 G:0.14634
position 3: T:0.48780 C:0.08711 A:0.20209 G:0.22300
Average T:0.41696 C:0.12892 A:0.25203 G:0.20209
#23: C77
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48084 C:0.10105 A:0.19512 G:0.22300
Average T:0.42160 C:0.13008 A:0.24971 G:0.19861
#24: C136
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09756 A:0.19512 G:0.22300
Average T:0.42276 C:0.12892 A:0.24971 G:0.19861
#25: C72
position 1: T:0.31707 C:0.11847 A:0.32753 G:0.23693
position 2: T:0.44599 C:0.18118 A:0.22648 G:0.14634
position 3: T:0.49477 C:0.08014 A:0.20209 G:0.22300
Average T:0.41928 C:0.12660 A:0.25203 G:0.20209
#26: C57
position 1: T:0.32056 C:0.11847 A:0.32753 G:0.23345
position 2: T:0.45645 C:0.17073 A:0.22648 G:0.14634
position 3: T:0.49826 C:0.06969 A:0.20906 G:0.22300
Average T:0.42509 C:0.11963 A:0.25436 G:0.20093
#27: C36
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09756 A:0.19164 G:0.22648
Average T:0.42276 C:0.12892 A:0.24855 G:0.19977
#28: C84
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09408 A:0.19512 G:0.22648
Average T:0.42276 C:0.12776 A:0.24971 G:0.19977
#29: C79
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09408 A:0.19512 G:0.22648
Average T:0.42276 C:0.12776 A:0.24971 G:0.19977
#30: C85
position 1: T:0.34146 C:0.10801 A:0.32404 G:0.22648
position 2: T:0.44251 C:0.18118 A:0.22997 G:0.14634
position 3: T:0.48432 C:0.09408 A:0.19512 G:0.22648
Average T:0.42276 C:0.12776 A:0.24971 G:0.19977
Sums of codon usage counts
------------------------------------------------------------------------------
Phe F TTT 548 | Ser S TCT 221 | Tyr Y TAT 550 | Cys C TGT 132
TTC 75 | TCC 49 | TAC 110 | TGC 48
Leu L TTA 155 | TCA 105 | *** * TAA 0 | *** * TGA 0
TTG 631 | TCG 15 | TAG 0 | Trp W TGG 210
------------------------------------------------------------------------------
Leu L CTT 326 | Pro P CCT 150 | His H CAT 108 | Arg R CGT 66
CTC 1 | CCC 0 | CAC 0 | CGC 54
CTA 30 | CCA 60 | Gln Q CAA 90 | CGA 0
CTG 47 | CCG 0 | CAG 42 | CGG 0
------------------------------------------------------------------------------
Ile I ATT 478 | Thr T ACT 268 | Asn N AAT 214 | Ser S AGT 150
ATC 18 | ACC 0 | AAC 146 | AGC 60
ATA 202 | ACA 275 | Lys K AAA 121 | Arg R AGA 118
Met M ATG 461 | ACG 33 | AAG 256 | AGG 3
------------------------------------------------------------------------------
Val V GTT 482 | Ala A GCT 189 | Asp D GAT 91 | Gly G GGT 238
GTC 57 | GCC 60 | GAC 0 | GGC 92
GTA 145 | GCA 130 | Glu E GAA 180 | GGA 90
GTG 171 | GCG 0 | GAG 59 | GGG 0
------------------------------------------------------------------------------
Codon position x base (3x4) table, overall
position 1: T:0.33089 C:0.11312 A:0.32555 G:0.23043
position 2: T:0.44448 C:0.18060 A:0.22846 G:0.14646
position 3: T:0.48908 C:0.08943 A:0.19756 G:0.22393
Average T:0.42149 C:0.12772 A:0.25052 G:0.20027
Model 1: NearlyNeutral (2 categories)
TREE # 1: (12, 25, (((17, 1), 22), 14), ((((((((11, 2, 23), 3, 24), 21, 27, (4, 30, 8, 9, 29, 28), 5, 19), 18), (16, 6)), (7, 10)), 13, 15), (26, 20))); MP score: 86
lnL(ntime: 45 np: 48): -1616.101155 +0.000000
31..12 31..25 31..32 32..33 33..34 34..17 34..1 33..22 32..14 31..35 35..36 36..37 37..38 38..39 39..40 40..41 41..42 42..11 42..2 42..23 41..3 41..24 40..21 40..27 40..43 43..4 43..30 43..8 43..9 43..29 43..28 40..5 40..19 39..18 38..44 44..16 44..6 37..45 45..7 45..10 36..13 36..15 35..46 46..26 46..20
0.000004 0.000004 0.004110 0.007381 0.003582 0.011451 0.003784 0.003874 0.023173 0.003784 0.003805 0.004119 0.098774 0.009779 0.003696 0.003674 0.003669 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.007415 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.007355 0.007418 0.024149 0.003665 0.000004 0.015551 0.007351 0.015827 0.023257 0.000004 0.003801 0.043270 0.000004 6.172672 0.881828 0.023527
Note: Branch length is defined as number of nucleotide substitutions per codon (not per neucleotide site).
tree length = 0.347790
(12: 0.000004, 25: 0.000004, (((17: 0.011451, 1: 0.003784): 0.003582, 22: 0.003874): 0.007381, 14: 0.023173): 0.004110, ((((((((11: 0.000004, 2: 0.000004, 23: 0.000004): 0.003669, 3: 0.000004, 24: 0.000004): 0.003674, 21: 0.000004, 27: 0.000004, (4: 0.000004, 30: 0.000004, 8: 0.000004, 9: 0.000004, 29: 0.000004, 28: 0.000004): 0.007415, 5: 0.000004, 19: 0.007355): 0.003696, 18: 0.007418): 0.009779, (16: 0.003665, 6: 0.000004): 0.024149): 0.098774, (7: 0.007351, 10: 0.015827): 0.015551): 0.004119, 13: 0.023257, 15: 0.000004): 0.003805, (26: 0.043270, 20: 0.000004): 0.003801): 0.003784);
(C216: 0.000004, C72: 0.000004, (((C113: 0.011451, C238: 0.003784): 0.003582, C242: 0.003874): 0.007381, C124: 0.023173): 0.004110, ((((((((C7: 0.000004, C60: 0.000004, C77: 0.000004): 0.003669, C281: 0.000004, C136: 0.000004): 0.003674, C11: 0.000004, C36: 0.000004, (C82: 0.000004, C85: 0.000004, C78: 0.000004, C93: 0.000004, C79: 0.000004, C84: 0.000004): 0.007415, C32: 0.000004, C131: 0.007355): 0.003696, C197: 0.007418): 0.009779, (C173: 0.003665, C178: 0.000004): 0.024149): 0.098774, (C71: 0.007351, C66: 0.015827): 0.015551): 0.004119, C53: 0.023257, C65: 0.000004): 0.003805, (C57: 0.043270, C130: 0.000004): 0.003801): 0.003784);
Detailed output identifying parameters
kappa (ts/tv) = 6.17267
MLEs of dN/dS (w) for site classes (K=2)
p: 0.88183 0.11817
w: 0.02353 1.00000
dN & dS for each branch
branch t N S dN/dS dN dS N*dN S*dS
31..12 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
31..25 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
31..32 0.004 680.4 180.6 0.1389 0.0006 0.0043 0.4 0.8
32..33 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
33..34 0.004 680.4 180.6 0.1389 0.0005 0.0037 0.4 0.7
34..17 0.011 680.4 180.6 0.1389 0.0017 0.0119 1.1 2.2
34..1 0.004 680.4 180.6 0.1389 0.0005 0.0039 0.4 0.7
33..22 0.004 680.4 180.6 0.1389 0.0006 0.0040 0.4 0.7
32..14 0.023 680.4 180.6 0.1389 0.0034 0.0242 2.3 4.4
31..35 0.004 680.4 180.6 0.1389 0.0005 0.0039 0.4 0.7
35..36 0.004 680.4 180.6 0.1389 0.0006 0.0040 0.4 0.7
36..37 0.004 680.4 180.6 0.1389 0.0006 0.0043 0.4 0.8
37..38 0.099 680.4 180.6 0.1389 0.0143 0.1030 9.7 18.6
38..39 0.010 680.4 180.6 0.1389 0.0014 0.0102 1.0 1.8
39..40 0.004 680.4 180.6 0.1389 0.0005 0.0039 0.4 0.7
40..41 0.004 680.4 180.6 0.1389 0.0005 0.0038 0.4 0.7
41..42 0.004 680.4 180.6 0.1389 0.0005 0.0038 0.4 0.7
42..11 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
42..2 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
42..23 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
41..3 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
41..24 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..21 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..27 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..43 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
43..4 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..30 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..8 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..9 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..29 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..28 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..5 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..19 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
39..18 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
38..44 0.024 680.4 180.6 0.1389 0.0035 0.0252 2.4 4.6
44..16 0.004 680.4 180.6 0.1389 0.0005 0.0038 0.4 0.7
44..6 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
37..45 0.016 680.4 180.6 0.1389 0.0023 0.0162 1.5 2.9
45..7 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
45..10 0.016 680.4 180.6 0.1389 0.0023 0.0165 1.6 3.0
36..13 0.023 680.4 180.6 0.1389 0.0034 0.0243 2.3 4.4
36..15 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
35..46 0.004 680.4 180.6 0.1389 0.0006 0.0040 0.4 0.7
46..26 0.043 680.4 180.6 0.1389 0.0063 0.0451 4.3 8.2
46..20 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
Time used: 3:07
Model 2: PositiveSelection (3 categories)
TREE # 1: (12, 25, (((17, 1), 22), 14), ((((((((11, 2, 23), 3, 24), 21, 27, (4, 30, 8, 9, 29, 28), 5, 19), 18), (16, 6)), (7, 10)), 13, 15), (26, 20))); MP score: 86
check convergence..
lnL(ntime: 45 np: 50): -1616.101155 +0.000000
31..12 31..25 31..32 32..33 33..34 34..17 34..1 33..22 32..14 31..35 35..36 36..37 37..38 38..39 39..40 40..41 41..42 42..11 42..2 42..23 41..3 41..24 40..21 40..27 40..43 43..4 43..30 43..8 43..9 43..29 43..28 40..5 40..19 39..18 38..44 44..16 44..6 37..45 45..7 45..10 36..13 36..15 35..46 46..26 46..20
0.000004 0.000004 0.004110 0.007381 0.003582 0.011451 0.003783 0.003874 0.023173 0.003784 0.003805 0.004119 0.098774 0.009779 0.003697 0.003674 0.003669 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.007415 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.007355 0.007418 0.024149 0.003665 0.000004 0.015551 0.007351 0.015827 0.023257 0.000004 0.003801 0.043270 0.000004 6.172735 0.881828 0.054484 0.023526 1.000000
Note: Branch length is defined as number of nucleotide substitutions per codon (not per neucleotide site).
tree length = 0.347791
(12: 0.000004, 25: 0.000004, (((17: 0.011451, 1: 0.003783): 0.003582, 22: 0.003874): 0.007381, 14: 0.023173): 0.004110, ((((((((11: 0.000004, 2: 0.000004, 23: 0.000004): 0.003669, 3: 0.000004, 24: 0.000004): 0.003674, 21: 0.000004, 27: 0.000004, (4: 0.000004, 30: 0.000004, 8: 0.000004, 9: 0.000004, 29: 0.000004, 28: 0.000004): 0.007415, 5: 0.000004, 19: 0.007355): 0.003697, 18: 0.007418): 0.009779, (16: 0.003665, 6: 0.000004): 0.024149): 0.098774, (7: 0.007351, 10: 0.015827): 0.015551): 0.004119, 13: 0.023257, 15: 0.000004): 0.003805, (26: 0.043270, 20: 0.000004): 0.003801): 0.003784);
(C216: 0.000004, C72: 0.000004, (((C113: 0.011451, C238: 0.003783): 0.003582, C242: 0.003874): 0.007381, C124: 0.023173): 0.004110, ((((((((C7: 0.000004, C60: 0.000004, C77: 0.000004): 0.003669, C281: 0.000004, C136: 0.000004): 0.003674, C11: 0.000004, C36: 0.000004, (C82: 0.000004, C85: 0.000004, C78: 0.000004, C93: 0.000004, C79: 0.000004, C84: 0.000004): 0.007415, C32: 0.000004, C131: 0.007355): 0.003697, C197: 0.007418): 0.009779, (C173: 0.003665, C178: 0.000004): 0.024149): 0.098774, (C71: 0.007351, C66: 0.015827): 0.015551): 0.004119, C53: 0.023257, C65: 0.000004): 0.003805, (C57: 0.043270, C130: 0.000004): 0.003801): 0.003784);
Detailed output identifying parameters
kappa (ts/tv) = 6.17273
MLEs of dN/dS (w) for site classes (K=3)
p: 0.88183 0.05448 0.06369
w: 0.02353 1.00000 1.00000
dN & dS for each branch
branch t N S dN/dS dN dS N*dN S*dS
31..12 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
31..25 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
31..32 0.004 680.4 180.6 0.1389 0.0006 0.0043 0.4 0.8
32..33 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
33..34 0.004 680.4 180.6 0.1389 0.0005 0.0037 0.4 0.7
34..17 0.011 680.4 180.6 0.1389 0.0017 0.0119 1.1 2.2
34..1 0.004 680.4 180.6 0.1389 0.0005 0.0039 0.4 0.7
33..22 0.004 680.4 180.6 0.1389 0.0006 0.0040 0.4 0.7
32..14 0.023 680.4 180.6 0.1389 0.0034 0.0242 2.3 4.4
31..35 0.004 680.4 180.6 0.1389 0.0005 0.0039 0.4 0.7
35..36 0.004 680.4 180.6 0.1389 0.0006 0.0040 0.4 0.7
36..37 0.004 680.4 180.6 0.1389 0.0006 0.0043 0.4 0.8
37..38 0.099 680.4 180.6 0.1389 0.0143 0.1030 9.7 18.6
38..39 0.010 680.4 180.6 0.1389 0.0014 0.0102 1.0 1.8
39..40 0.004 680.4 180.6 0.1389 0.0005 0.0039 0.4 0.7
40..41 0.004 680.4 180.6 0.1389 0.0005 0.0038 0.4 0.7
41..42 0.004 680.4 180.6 0.1389 0.0005 0.0038 0.4 0.7
42..11 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
42..2 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
42..23 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
41..3 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
41..24 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..21 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..27 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..43 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
43..4 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..30 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..8 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..9 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..29 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
43..28 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..5 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
40..19 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
39..18 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
38..44 0.024 680.4 180.6 0.1389 0.0035 0.0252 2.4 4.6
44..16 0.004 680.4 180.6 0.1389 0.0005 0.0038 0.4 0.7
44..6 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
37..45 0.016 680.4 180.6 0.1389 0.0023 0.0162 1.5 2.9
45..7 0.007 680.4 180.6 0.1389 0.0011 0.0077 0.7 1.4
45..10 0.016 680.4 180.6 0.1389 0.0023 0.0165 1.6 3.0
36..13 0.023 680.4 180.6 0.1389 0.0034 0.0243 2.3 4.4
36..15 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
35..46 0.004 680.4 180.6 0.1389 0.0006 0.0040 0.4 0.7
46..26 0.043 680.4 180.6 0.1389 0.0063 0.0451 4.3 8.2
46..20 0.000 680.4 180.6 0.1389 0.0000 0.0000 0.0 0.0
Naive Empirical Bayes (NEB) analysis
Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118)
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: C238)
Pr(w>1) post mean +- SE for w
7 V 0.505 1.277 +- 0.579
121 I 0.560 1.352 +- 0.594
183 A 0.612 1.420 +- 0.615
The grid (see ternary graph for p0-p1)
w0: 0.050 0.150 0.250 0.350 0.450 0.550 0.650 0.750 0.850 0.950
w2: 1.500 2.500 3.500 4.500 5.500 6.500 7.500 8.500 9.500 10.500
Posterior on the grid
w0: 0.999 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
w2: 0.827 0.145 0.021 0.004 0.001 0.001 0.000 0.000 0.000 0.000
Posterior for p0-p1 (see the ternary graph) (YWN2015, fig. 1)
0.000
0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.055
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.003 0.115 0.827
sum of density on p0-p1 = 1.000000
Time used: 7:52
Model 7: beta (10 categories)
TREE # 1: (12, 25, (((17, 1), 22), 14), ((((((((11, 2, 23), 3, 24), 21, 27, (4, 30, 8, 9, 29, 28), 5, 19), 18), (16, 6)), (7, 10)), 13, 15), (26, 20))); MP score: 86
check convergence..
lnL(ntime: 45 np: 48): -1615.595872 +0.000000
31..12 31..25 31..32 32..33 33..34 34..17 34..1 33..22 32..14 31..35 35..36 36..37 37..38 38..39 39..40 40..41 41..42 42..11 42..2 42..23 41..3 41..24 40..21 40..27 40..43 43..4 43..30 43..8 43..9 43..29 43..28 40..5 40..19 39..18 38..44 44..16 44..6 37..45 45..7 45..10 36..13 36..15 35..46 46..26 46..20
0.000004 0.000004 0.004114 0.007366 0.003574 0.011446 0.003788 0.003873 0.023156 0.003784 0.003806 0.004105 0.098046 0.009779 0.003685 0.003665 0.003660 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.007387 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.007336 0.007398 0.024054 0.003665 0.000004 0.015575 0.007329 0.015855 0.023279 0.000004 0.003802 0.043199 0.000004 6.109824 0.088404 0.629983
Note: Branch length is defined as number of nucleotide substitutions per codon (not per neucleotide site).
tree length = 0.346801
(12: 0.000004, 25: 0.000004, (((17: 0.011446, 1: 0.003788): 0.003574, 22: 0.003873): 0.007366, 14: 0.023156): 0.004114, ((((((((11: 0.000004, 2: 0.000004, 23: 0.000004): 0.003660, 3: 0.000004, 24: 0.000004): 0.003665, 21: 0.000004, 27: 0.000004, (4: 0.000004, 30: 0.000004, 8: 0.000004, 9: 0.000004, 29: 0.000004, 28: 0.000004): 0.007387, 5: 0.000004, 19: 0.007336): 0.003685, 18: 0.007398): 0.009779, (16: 0.003665, 6: 0.000004): 0.024054): 0.098046, (7: 0.007329, 10: 0.015855): 0.015575): 0.004105, 13: 0.023279, 15: 0.000004): 0.003806, (26: 0.043199, 20: 0.000004): 0.003802): 0.003784);
(C216: 0.000004, C72: 0.000004, (((C113: 0.011446, C238: 0.003788): 0.003574, C242: 0.003873): 0.007366, C124: 0.023156): 0.004114, ((((((((C7: 0.000004, C60: 0.000004, C77: 0.000004): 0.003660, C281: 0.000004, C136: 0.000004): 0.003665, C11: 0.000004, C36: 0.000004, (C82: 0.000004, C85: 0.000004, C78: 0.000004, C93: 0.000004, C79: 0.000004, C84: 0.000004): 0.007387, C32: 0.000004, C131: 0.007336): 0.003685, C197: 0.007398): 0.009779, (C173: 0.003665, C178: 0.000004): 0.024054): 0.098046, (C71: 0.007329, C66: 0.015855): 0.015575): 0.004105, C53: 0.023279, C65: 0.000004): 0.003806, (C57: 0.043199, C130: 0.000004): 0.003802): 0.003784);
Detailed output identifying parameters
kappa (ts/tv) = 6.10982
Parameters in M7 (beta):
p = 0.08840 q = 0.62998
MLEs of dN/dS (w) for site classes (K=10)
p: 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000
w: 0.00000 0.00000 0.00000 0.00002 0.00026 0.00255 0.01677 0.08268 0.31116 0.80698
dN & dS for each branch
branch t N S dN/dS dN dS N*dN S*dS
31..12 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
31..25 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
31..32 0.004 680.6 180.4 0.1220 0.0005 0.0045 0.4 0.8
32..33 0.007 680.6 180.4 0.1220 0.0010 0.0080 0.7 1.4
33..34 0.004 680.6 180.4 0.1220 0.0005 0.0039 0.3 0.7
34..17 0.011 680.6 180.4 0.1220 0.0015 0.0125 1.0 2.2
34..1 0.004 680.6 180.4 0.1220 0.0005 0.0041 0.3 0.7
33..22 0.004 680.6 180.4 0.1220 0.0005 0.0042 0.4 0.8
32..14 0.023 680.6 180.4 0.1220 0.0031 0.0252 2.1 4.6
31..35 0.004 680.6 180.4 0.1220 0.0005 0.0041 0.3 0.7
35..36 0.004 680.6 180.4 0.1220 0.0005 0.0041 0.3 0.7
36..37 0.004 680.6 180.4 0.1220 0.0005 0.0045 0.4 0.8
37..38 0.098 680.6 180.4 0.1220 0.0130 0.1068 8.9 19.3
38..39 0.010 680.6 180.4 0.1220 0.0013 0.0107 0.9 1.9
39..40 0.004 680.6 180.4 0.1220 0.0005 0.0040 0.3 0.7
40..41 0.004 680.6 180.4 0.1220 0.0005 0.0040 0.3 0.7
41..42 0.004 680.6 180.4 0.1220 0.0005 0.0040 0.3 0.7
42..11 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
42..2 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
42..23 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
41..3 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
41..24 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..21 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..27 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..43 0.007 680.6 180.4 0.1220 0.0010 0.0080 0.7 1.5
43..4 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..30 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..8 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..9 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..29 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..28 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..5 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..19 0.007 680.6 180.4 0.1220 0.0010 0.0080 0.7 1.4
39..18 0.007 680.6 180.4 0.1220 0.0010 0.0081 0.7 1.5
38..44 0.024 680.6 180.4 0.1220 0.0032 0.0262 2.2 4.7
44..16 0.004 680.6 180.4 0.1220 0.0005 0.0040 0.3 0.7
44..6 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
37..45 0.016 680.6 180.4 0.1220 0.0021 0.0170 1.4 3.1
45..7 0.007 680.6 180.4 0.1220 0.0010 0.0080 0.7 1.4
45..10 0.016 680.6 180.4 0.1220 0.0021 0.0173 1.4 3.1
36..13 0.023 680.6 180.4 0.1220 0.0031 0.0254 2.1 4.6
36..15 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
35..46 0.004 680.6 180.4 0.1220 0.0005 0.0041 0.3 0.7
46..26 0.043 680.6 180.4 0.1220 0.0057 0.0471 3.9 8.5
46..20 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
Time used: 26:26
Model 8: beta&w>1 (11 categories)
TREE # 1: (12, 25, (((17, 1), 22), 14), ((((((((11, 2, 23), 3, 24), 21, 27, (4, 30, 8, 9, 29, 28), 5, 19), 18), (16, 6)), (7, 10)), 13, 15), (26, 20))); MP score: 86
lnL(ntime: 45 np: 50): -1615.595872 +0.000000
31..12 31..25 31..32 32..33 33..34 34..17 34..1 33..22 32..14 31..35 35..36 36..37 37..38 38..39 39..40 40..41 41..42 42..11 42..2 42..23 41..3 41..24 40..21 40..27 40..43 43..4 43..30 43..8 43..9 43..29 43..28 40..5 40..19 39..18 38..44 44..16 44..6 37..45 45..7 45..10 36..13 36..15 35..46 46..26 46..20
0.000004 0.000004 0.004114 0.007366 0.003574 0.011446 0.003788 0.003873 0.023156 0.003784 0.003806 0.004105 0.098046 0.009779 0.003685 0.003665 0.003660 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.007387 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.000004 0.007336 0.007398 0.024054 0.003665 0.000004 0.015575 0.007329 0.015855 0.023279 0.000004 0.003802 0.043199 0.000004 6.109848 0.999990 0.088404 0.630029 1.000000
Note: Branch length is defined as number of nucleotide substitutions per codon (not per neucleotide site).
tree length = 0.346801
(12: 0.000004, 25: 0.000004, (((17: 0.011446, 1: 0.003788): 0.003574, 22: 0.003873): 0.007366, 14: 0.023156): 0.004114, ((((((((11: 0.000004, 2: 0.000004, 23: 0.000004): 0.003660, 3: 0.000004, 24: 0.000004): 0.003665, 21: 0.000004, 27: 0.000004, (4: 0.000004, 30: 0.000004, 8: 0.000004, 9: 0.000004, 29: 0.000004, 28: 0.000004): 0.007387, 5: 0.000004, 19: 0.007336): 0.003685, 18: 0.007398): 0.009779, (16: 0.003665, 6: 0.000004): 0.024054): 0.098046, (7: 0.007329, 10: 0.015855): 0.015575): 0.004105, 13: 0.023279, 15: 0.000004): 0.003806, (26: 0.043199, 20: 0.000004): 0.003802): 0.003784);
(C216: 0.000004, C72: 0.000004, (((C113: 0.011446, C238: 0.003788): 0.003574, C242: 0.003873): 0.007366, C124: 0.023156): 0.004114, ((((((((C7: 0.000004, C60: 0.000004, C77: 0.000004): 0.003660, C281: 0.000004, C136: 0.000004): 0.003665, C11: 0.000004, C36: 0.000004, (C82: 0.000004, C85: 0.000004, C78: 0.000004, C93: 0.000004, C79: 0.000004, C84: 0.000004): 0.007387, C32: 0.000004, C131: 0.007336): 0.003685, C197: 0.007398): 0.009779, (C173: 0.003665, C178: 0.000004): 0.024054): 0.098046, (C71: 0.007329, C66: 0.015855): 0.015575): 0.004105, C53: 0.023279, C65: 0.000004): 0.003806, (C57: 0.043199, C130: 0.000004): 0.003802): 0.003784);
Detailed output identifying parameters
kappa (ts/tv) = 6.10985
Parameters in M8 (beta&w>1):
p0 = 0.99999 p = 0.08840 q = 0.63003
(p1 = 0.00001) w = 1.00000
MLEs of dN/dS (w) for site classes (K=11)
p: 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.00001
w: 0.00000 0.00000 0.00000 0.00002 0.00026 0.00255 0.01676 0.08267 0.31113 0.80694 1.00000
dN & dS for each branch
branch t N S dN/dS dN dS N*dN S*dS
31..12 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
31..25 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
31..32 0.004 680.6 180.4 0.1220 0.0005 0.0045 0.4 0.8
32..33 0.007 680.6 180.4 0.1220 0.0010 0.0080 0.7 1.4
33..34 0.004 680.6 180.4 0.1220 0.0005 0.0039 0.3 0.7
34..17 0.011 680.6 180.4 0.1220 0.0015 0.0125 1.0 2.2
34..1 0.004 680.6 180.4 0.1220 0.0005 0.0041 0.3 0.7
33..22 0.004 680.6 180.4 0.1220 0.0005 0.0042 0.4 0.8
32..14 0.023 680.6 180.4 0.1220 0.0031 0.0252 2.1 4.6
31..35 0.004 680.6 180.4 0.1220 0.0005 0.0041 0.3 0.7
35..36 0.004 680.6 180.4 0.1220 0.0005 0.0041 0.3 0.7
36..37 0.004 680.6 180.4 0.1220 0.0005 0.0045 0.4 0.8
37..38 0.098 680.6 180.4 0.1220 0.0130 0.1068 8.9 19.3
38..39 0.010 680.6 180.4 0.1220 0.0013 0.0107 0.9 1.9
39..40 0.004 680.6 180.4 0.1220 0.0005 0.0040 0.3 0.7
40..41 0.004 680.6 180.4 0.1220 0.0005 0.0040 0.3 0.7
41..42 0.004 680.6 180.4 0.1220 0.0005 0.0040 0.3 0.7
42..11 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
42..2 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
42..23 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
41..3 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
41..24 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..21 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..27 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..43 0.007 680.6 180.4 0.1220 0.0010 0.0080 0.7 1.5
43..4 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..30 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..8 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..9 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..29 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
43..28 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..5 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
40..19 0.007 680.6 180.4 0.1220 0.0010 0.0080 0.7 1.4
39..18 0.007 680.6 180.4 0.1220 0.0010 0.0081 0.7 1.5
38..44 0.024 680.6 180.4 0.1220 0.0032 0.0262 2.2 4.7
44..16 0.004 680.6 180.4 0.1220 0.0005 0.0040 0.3 0.7
44..6 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
37..45 0.016 680.6 180.4 0.1220 0.0021 0.0170 1.4 3.1
45..7 0.007 680.6 180.4 0.1220 0.0010 0.0080 0.7 1.4
45..10 0.016 680.6 180.4 0.1220 0.0021 0.0173 1.4 3.1
36..13 0.023 680.6 180.4 0.1220 0.0031 0.0254 2.1 4.6
36..15 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
35..46 0.004 680.6 180.4 0.1220 0.0005 0.0041 0.3 0.7
46..26 0.043 680.6 180.4 0.1220 0.0057 0.0471 3.9 8.5
46..20 0.000 680.6 180.4 0.1220 0.0000 0.0000 0.0 0.0
Naive Empirical Bayes (NEB) analysis
Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118)
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: C238)
Pr(w>1) post mean +- SE for w
7 V 0.576 1.112 +- 0.620
71 I 0.502 1.014 +- 0.623
121 I 0.651 1.210 +- 0.606
178 A 0.524 1.043 +- 0.622
183 A 0.719 1.295 +- 0.581
The grid
p0: 0.050 0.150 0.250 0.350 0.450 0.550 0.650 0.750 0.850 0.950
p : 0.100 0.300 0.500 0.700 0.900 1.100 1.300 1.500 1.700 1.900
q : 0.100 0.300 0.500 0.700 0.900 1.100 1.300 1.500 1.700 1.900
ws: 1.500 2.500 3.500 4.500 5.500 6.500 7.500 8.500 9.500 10.500
Posterior on the grid
p0: 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000
p : 0.995 0.005 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
q : 0.000 0.000 0.000 0.008 0.039 0.090 0.147 0.199 0.242 0.275
ws: 0.919 0.074 0.006 0.001 0.000 0.000 0.000 0.000 0.000 0.000
Time used: 49:21
Model 1: NearlyNeutral -1616.101155 Model 2: PositiveSelection -1616.101155 Model 7: beta -1615.595872 Model 8: beta&w>1 -1615.595872 Model 2 vs 1 0 Model 8 vs 7 0
Not all of the following information may be relevant for the case being handled, since this project may be part of a much larger auto-PSS-genome project where several methods of detection of positively selected sites have been used. As such the aligned.score_ascii file may have more sequences than the file effectively used to detect positively selected codons, since the content of this file reflects the content of the file used for the master alignment, from which a subsample may have been taken. # ### General parameters ### # # The maximum number of sequences to use for the master file sequence_limit=90 # The random seed random_seed=3976763 # ### Alignment ### # # The alignment method: clustalw, muscle, kalign, t_coffee, or amap align_method=muscle # Minimum support value for amino acid positions in the alignment tcoffee_min_score=3 # ### MrBayes ### # # Number of iterations in MrBayes mrbayes_generations=1000000 # MrBayes burnin mrbayes_burnin=2500 # ### FUBAR ### # # The maximum number of sequences to be used by FUBAR. fubar_sequence_limit=90 # The number of FUBAR runs fubar_runs=1 # ### codeML ### # # The maximum number of sequences to be used by CodeML codeml_sequence_limit=30 # The number of CodeML runs codeml_runs=1 # The CodeML models to be run, one or more of: '1', '2', '7', and/or '8'. codeml_models=1 2 7 8 # ### OmegaMap ### # # The maximum number of sequences to use in OmegaMap omegamap_sequence_limit=90 # The number of OmegaMap runs omegamap_runs=1 # The number of OmegaMap iterations omegamap_iterations=2500
Phone: +351 220 408 800
Email: info@i3s.up.pt
Address: Rua Alfredo Allen, 208
4200-135 Porto, Portugal
If you use B+, please cite us:
N. Vázquez, C.P. Vieira, B.S.R. Amorin, A. Torres, H. López-Fernández, F. Fdez-Riverola, J.L.R. Sousa, M. Reboiro-Jato, J. Vieira (2018) Large Scale Analyses and Visualization of Adaptive Amino Acid Changes Projects. Interdisciplinary Sciences: Computational Life Sciences. https://doi.org/10.1007/s12539-018-0282-7
N. Vázquez, C.P. Vieira, B.S.R. Amorin, A. Torres, H. López-Fernández, F. Fdez-Riverola, J.L.R. Sousa, M. Reboiro-Jato, J. Vieira (2017) Automated Collection and Sharing of Adaptive Amino Acid Changes Data. 11th International Conference on Practical Applications of Computational Biology & Bioinformatics. Porto, Portugal. https://doi.org/10.1007/978-3-319-60816-7_3
