--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 15:15:29 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/1/14-3-3zeta-PK/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PK/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PK/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/1/14-3-3zeta-PK/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1340.45 -1378.43
2 -1341.44 -1382.88
--------------------------------------
TOTAL -1340.83 -1382.19
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PK/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PK/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/1/14-3-3zeta-PK/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.471711 0.063859 0.136821 0.983478 0.398510 801.80 816.60 1.002
r(A<->C){all} 0.069978 0.001603 0.003157 0.144533 0.062458 373.38 457.65 1.000
r(A<->G){all} 0.235400 0.015768 0.036986 0.487003 0.210911 91.65 141.13 1.004
r(A<->T){all} 0.068214 0.001666 0.002314 0.143659 0.061539 529.97 574.26 1.003
r(C<->G){all} 0.046793 0.000925 0.004307 0.111149 0.040739 556.36 596.22 1.000
r(C<->T){all} 0.562685 0.022441 0.274033 0.837872 0.566693 102.21 149.75 1.005
r(G<->T){all} 0.016930 0.000305 0.000019 0.052410 0.011032 618.63 650.99 1.000
pi(A){all} 0.280404 0.000256 0.249159 0.310324 0.280458 1057.32 1139.05 1.000
pi(C){all} 0.258927 0.000248 0.227280 0.288890 0.258744 1254.37 1272.37 1.000
pi(G){all} 0.260526 0.000236 0.231890 0.291584 0.260219 917.50 1058.24 1.000
pi(T){all} 0.200143 0.000212 0.169008 0.226582 0.200361 899.95 1077.76 1.000
alpha{1,2} 0.092961 0.000848 0.025787 0.152799 0.091089 1059.05 1105.64 1.001
alpha{3} 1.224562 0.431418 0.217476 2.446944 1.082673 985.67 1034.49 1.002
pinvar{all} 0.824929 0.001223 0.750923 0.884185 0.829828 1076.42 1119.47 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 -1263.066771
Model 2: PositiveSelection -1263.066771
Model 0: one-ratio -1264.026193
Model 3: discrete -1263.063085
Model 7: beta -1263.3924
Model 8: beta&w>1 -1263.066768
Model 0 vs 1 1.9188439999998081
Model 2 vs 1 0.0
Model 8 vs 7 0.6512640000000829
