--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 13:35:40 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-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PC/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-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1309.29 -1348.08
2 -1310.76 -1347.38
--------------------------------------
TOTAL -1309.77 -1347.79
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PC/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-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.765111 0.166174 0.148443 1.551500 0.690985 660.91 696.87 1.000
r(A<->C){all} 0.075164 0.001965 0.005343 0.160495 0.068080 308.73 368.35 1.000
r(A<->G){all} 0.181657 0.012948 0.020501 0.414235 0.158441 207.47 216.11 1.000
r(A<->T){all} 0.053634 0.001680 0.000088 0.131582 0.044321 383.12 430.90 1.000
r(C<->G){all} 0.044690 0.000961 0.000066 0.105612 0.037496 450.69 470.50 1.001
r(C<->T){all} 0.624717 0.022601 0.348430 0.907682 0.630729 173.95 179.98 1.000
r(G<->T){all} 0.020138 0.000453 0.000024 0.063515 0.013388 359.28 411.36 1.001
pi(A){all} 0.287291 0.000265 0.257842 0.321432 0.287098 1195.79 1230.81 1.000
pi(C){all} 0.257272 0.000258 0.224178 0.287263 0.256994 1068.78 1205.46 1.000
pi(G){all} 0.257247 0.000261 0.227363 0.289712 0.257252 1159.19 1201.43 1.000
pi(T){all} 0.198191 0.000207 0.171397 0.226982 0.198188 1180.63 1304.12 1.000
alpha{1,2} 0.089389 0.000597 0.049461 0.138820 0.085504 924.19 1066.04 1.000
alpha{3} 0.783188 0.264595 0.089797 1.808021 0.655387 677.42 804.51 1.000
pinvar{all} 0.853751 0.000916 0.794113 0.906563 0.858097 827.73 927.03 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 -1225.465062
Model 2: PositiveSelection -1225.456381
Model 0: one-ratio -1226.517883
Model 3: discrete -1225.456381
Model 7: beta -1225.818465
Model 8: beta&w>1 -1225.456377
Model 0 vs 1 2.105641999999989
Model 2 vs 1 0.017362000000048283
Model 8 vs 7 0.7241760000001705
