--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Nov 12 06:00:54 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
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/ADOPS/200/CG9485-PE/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/200/CG9485-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/200/CG9485-PE/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/200/CG9485-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -18442.35 -18458.82
2 -18442.08 -18461.12
--------------------------------------
TOTAL -18442.20 -18460.52
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/200/CG9485-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/200/CG9485-PE/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/200/CG9485-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.443493 0.002399 1.347477 1.536372 1.443360 1355.73 1406.92 1.001
r(A<->C){all} 0.096105 0.000059 0.081506 0.111075 0.095845 779.75 806.47 1.000
r(A<->G){all} 0.278755 0.000185 0.253583 0.305420 0.278557 820.63 854.57 1.000
r(A<->T){all} 0.119692 0.000112 0.099913 0.141759 0.119314 885.79 960.53 1.000
r(C<->G){all} 0.044835 0.000019 0.037216 0.054293 0.044761 865.02 885.52 1.001
r(C<->T){all} 0.383447 0.000218 0.356730 0.413327 0.383443 779.95 786.80 1.000
r(G<->T){all} 0.077166 0.000047 0.064335 0.090396 0.077073 964.18 1107.37 1.000
pi(A){all} 0.217635 0.000035 0.206537 0.229389 0.217504 877.20 970.07 1.000
pi(C){all} 0.290079 0.000037 0.279033 0.302627 0.289904 808.61 922.94 1.000
pi(G){all} 0.277126 0.000037 0.264609 0.288545 0.277074 1175.07 1207.30 1.001
pi(T){all} 0.215159 0.000029 0.204851 0.225547 0.215108 881.22 953.46 1.003
alpha{1,2} 0.129043 0.000033 0.117349 0.140089 0.128760 1436.82 1452.52 1.000
alpha{3} 6.304459 1.210395 4.360364 8.443409 6.191276 1491.93 1496.46 1.000
pinvar{all} 0.313402 0.000318 0.278929 0.348552 0.313513 1135.10 1191.35 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 -17318.601925
Model 2: PositiveSelection -17318.602128
Model 0: one-ratio -17455.212255
Model 3: discrete -17250.559313
Model 7: beta -17252.27484
Model 8: beta&w>1 -17251.474405
Model 0 vs 1 273.22065999999904
Model 2 vs 1 4.059999992023222E-4
Model 8 vs 7 1.6008699999947567
