--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sun Oct 01 00:01:48 WEST 2017
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=
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/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/Batch_1_ADOPS/Zika-pr/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1481.10 -1543.08
2 -1485.10 -1536.53
--------------------------------------
TOTAL -1481.77 -1542.39
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-pr/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/Batch_1_ADOPS/Zika-pr/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 14.231963 1.678351 11.762970 16.860310 14.190420 933.64 1023.20 1.001
r(A<->C){all} 0.065258 0.000499 0.022748 0.108233 0.063034 625.73 676.05 1.000
r(A<->G){all} 0.279692 0.003585 0.172386 0.401717 0.277969 269.74 386.90 1.003
r(A<->T){all} 0.038043 0.000241 0.011182 0.068969 0.036023 717.87 734.73 1.000
r(C<->G){all} 0.010499 0.000071 0.000018 0.027123 0.008486 714.40 788.34 1.000
r(C<->T){all} 0.582008 0.004420 0.450093 0.709147 0.583276 273.11 365.03 1.003
r(G<->T){all} 0.024501 0.000118 0.005836 0.045555 0.022937 730.84 739.12 1.002
pi(A){all} 0.280625 0.000597 0.236761 0.332002 0.279752 766.99 917.04 1.000
pi(C){all} 0.205546 0.000434 0.165678 0.246583 0.204474 483.94 728.75 1.001
pi(G){all} 0.288735 0.000589 0.243707 0.338181 0.288211 1028.29 1062.03 1.002
pi(T){all} 0.225094 0.000508 0.184942 0.272649 0.224367 712.00 824.16 1.000
alpha{1,2} 0.083988 0.000026 0.073554 0.093405 0.083735 1185.65 1189.14 1.001
alpha{3} 0.320268 0.002857 0.251928 0.429815 0.318345 186.78 703.29 1.014
pinvar{all} 0.178474 0.003923 0.054999 0.295093 0.179513 885.70 994.27 1.004
------------------------------------------------------------------------------------------------------
* 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 -1242.129723
Model 2: PositiveSelection -1242.13823
Model 0: one-ratio -1242.13823
Model 3: discrete -1237.217799
Model 7: beta -1237.774059
Model 8: beta&w>1 -1237.774377
Model 0 vs 1 0.017014000000017404
Model 2 vs 1 0.017014000000017404
Model 8 vs 7 6.359999997584964E-4
