--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 14:38:42 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-PH/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PH/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PH/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-PH/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1543.62 -1567.77
2 -1544.11 -1563.81
--------------------------------------
TOTAL -1543.84 -1567.10
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PH/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PH/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-PH/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.246494 0.001602 0.173031 0.324009 0.242767 1103.27 1122.88 1.000
r(A<->C){all} 0.111299 0.001137 0.051950 0.178245 0.107781 894.11 919.19 1.000
r(A<->G){all} 0.154615 0.001757 0.080753 0.237992 0.150392 694.22 813.52 1.000
r(A<->T){all} 0.065836 0.000992 0.010529 0.126475 0.061315 639.84 780.68 1.001
r(C<->G){all} 0.063359 0.000685 0.018397 0.115967 0.059883 966.47 1016.17 1.000
r(C<->T){all} 0.555121 0.004818 0.424696 0.693123 0.555175 577.68 640.20 1.000
r(G<->T){all} 0.049770 0.000752 0.007372 0.103628 0.044993 795.45 824.71 1.000
pi(A){all} 0.286651 0.000249 0.256314 0.317695 0.286463 1034.46 1123.43 1.000
pi(C){all} 0.261095 0.000240 0.232054 0.291559 0.260862 1223.63 1349.92 1.001
pi(G){all} 0.257423 0.000243 0.226461 0.286314 0.257530 1180.10 1329.71 1.003
pi(T){all} 0.194831 0.000186 0.168107 0.220922 0.194652 1170.56 1249.17 1.000
alpha{1,2} 0.057616 0.001809 0.000105 0.133641 0.051188 951.75 1130.46 1.000
alpha{3} 2.056245 0.633411 0.705016 3.648509 1.921707 1236.79 1368.89 1.000
pinvar{all} 0.475315 0.008296 0.295716 0.642704 0.485554 870.98 1115.57 1.001
------------------------------------------------------------------------------------------------------
* 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 -1451.36118
Model 2: PositiveSelection -1451.36118
Model 0: one-ratio -1458.92382
Model 3: discrete -1451.332921
Model 7: beta -1451.333746
Model 8: beta&w>1 -1451.361179
Model 0 vs 1 15.125279999999748
Model 2 vs 1 0.0
Model 8 vs 7 0.054865999999947235
