--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 14:09:41 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-PF/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PF/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-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1309.54 -1349.51
2 -1309.56 -1346.69
--------------------------------------
TOTAL -1309.55 -1348.87
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PF/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-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.773171 0.183746 0.131319 1.555523 0.690411 663.42 688.18 1.000
r(A<->C){all} 0.076535 0.002012 0.001789 0.161277 0.069540 462.70 489.46 1.001
r(A<->G){all} 0.184582 0.011134 0.020620 0.390947 0.167742 212.49 231.45 1.002
r(A<->T){all} 0.057489 0.001708 0.000097 0.134465 0.048918 377.68 445.33 1.004
r(C<->G){all} 0.047575 0.001074 0.000793 0.112710 0.040204 431.71 433.92 1.001
r(C<->T){all} 0.612294 0.021431 0.353034 0.902968 0.619312 213.30 224.03 1.002
r(G<->T){all} 0.021526 0.000482 0.000014 0.064504 0.014852 601.31 750.46 1.000
pi(A){all} 0.287230 0.000269 0.256960 0.320471 0.286909 1068.07 1074.44 1.000
pi(C){all} 0.257498 0.000247 0.227803 0.288917 0.257218 1026.46 1151.09 1.000
pi(G){all} 0.257149 0.000252 0.225835 0.287693 0.257058 1164.42 1248.35 1.000
pi(T){all} 0.198123 0.000200 0.170892 0.225212 0.197553 1054.69 1148.15 1.000
alpha{1,2} 0.088992 0.000625 0.051868 0.147356 0.085145 599.85 891.91 1.000
alpha{3} 0.762185 0.259295 0.077749 1.735662 0.631283 704.62 757.91 1.000
pinvar{all} 0.853421 0.001031 0.787751 0.908532 0.857633 767.83 969.32 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 -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
