--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed Feb 17 00:56:01 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=MUSCLE
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=/usr/bin/
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb
tcoffee.bin=t_coffee
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p":
(Use the harmonic mean for Bayes factor comparisons of models)
(Values are saved to the file /opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -9155.96 -9247.68
2 -9154.07 -9238.00
--------------------------------------
TOTAL -9154.62 -9246.99
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.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 "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.119654 0.003470 1.003076 1.232045 1.117332 714.32 750.83 1.000
r(A<->C){all} 0.023124 0.000020 0.014547 0.031631 0.022844 599.65 717.76 1.000
r(A<->G){all} 0.215361 0.000427 0.175094 0.255568 0.214306 356.15 386.78 1.000
r(A<->T){all} 0.020253 0.000024 0.011388 0.030361 0.019853 630.81 701.16 1.001
r(C<->G){all} 0.003003 0.000003 0.000164 0.006245 0.002767 795.64 818.83 1.000
r(C<->T){all} 0.716584 0.000547 0.670195 0.760399 0.717576 334.65 360.29 1.000
r(G<->T){all} 0.021675 0.000020 0.013935 0.031223 0.021332 682.28 718.14 1.000
pi(A){all} 0.280519 0.000062 0.264520 0.295282 0.280289 924.08 1014.58 1.002
pi(C){all} 0.227629 0.000052 0.213053 0.241120 0.227444 908.07 995.75 1.002
pi(G){all} 0.295418 0.000068 0.278933 0.311877 0.295459 979.54 1032.45 1.000
pi(T){all} 0.196434 0.000045 0.182725 0.208846 0.196381 684.82 887.79 1.000
alpha{1,2} 0.116468 0.000068 0.101205 0.133228 0.116085 1166.94 1190.04 1.000
alpha{3} 5.063851 1.150929 3.116586 7.164913 4.963227 1238.93 1344.24 1.000
pinvar{all} 0.303283 0.000726 0.248076 0.353593 0.303840 724.25 913.15 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
--- CODEML SUMMARY
Model 1: NearlyNeutral -8535.980608
Model 2: PositiveSelection -8535.980632
Model 0: one-ratio -8571.24262
Model 3: discrete -8529.52584
Model 7: beta -8529.594999
Model 8: beta&w>1 -8529.595061
Model 0 vs 1 70.5240240000021
Model 2 vs 1 4.8000001697801054E-5
Model 8 vs 7 1.2399999832268804E-4
