--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu May 31 07:29:13 WEST 2018
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=
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb_adops
tcoffee.bin=t_coffee_ADOPS
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS1/DNG_A1/NS2A_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS2A_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/ADOPS1/DNG_A1/NS2A_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -7651.79         -7706.68
2      -7652.72         -7702.79
--------------------------------------
TOTAL    -7652.15         -7706.01
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS2A_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/ADOPS1/DNG_A1/NS2A_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}        10.708158    0.506082    9.325163   12.085060   10.670070    712.81    782.59    1.000
r(A<->C){all}   0.049607    0.000063    0.034672    0.065998    0.049398    779.48    808.99    1.002
r(A<->G){all}   0.244089    0.000327    0.209844    0.280030    0.243436    565.75    567.53    1.003
r(A<->T){all}   0.046806    0.000047    0.032799    0.059534    0.046482    771.57    917.46    1.001
r(C<->G){all}   0.034281    0.000063    0.019848    0.050749    0.034049    589.02    710.67    1.000
r(C<->T){all}   0.589565    0.000464    0.545501    0.628685    0.590270    500.21    512.35    1.003
r(G<->T){all}   0.035653    0.000053    0.022110    0.050254    0.035356    820.31    878.36    1.000
pi(A){all}      0.310590    0.000119    0.288218    0.330565    0.310709    855.33    882.73    1.000
pi(C){all}      0.206980    0.000084    0.189792    0.224857    0.206842    575.13    706.45    1.000
pi(G){all}      0.239191    0.000099    0.221005    0.260202    0.238909    713.15    794.33    1.001
pi(T){all}      0.243239    0.000103    0.225059    0.264341    0.243060    790.72    822.12    1.002
alpha{1,2}      0.401019    0.001716    0.328601    0.488603    0.396587   1205.41   1219.01    1.001
alpha{3}        4.940137    1.058605    3.092832    6.899818    4.842345   1012.36   1167.00    1.000
pinvar{all}     0.034583    0.000396    0.000017    0.070242    0.031735   1169.72   1219.17    1.002
------------------------------------------------------------------------------------------------------
* 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	-7383.430627
Model 2: PositiveSelection	-7383.430627
Model 0: one-ratio	-7388.515064
Model 3: discrete	-7300.767982
Model 7: beta	-7302.928315
Model 8: beta&w>1	-7302.929901


Model 0 vs 1	10.16887400000087

Model 2 vs 1	0.0

Model 8 vs 7	0.0031720000006316695