--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 21:21:20 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/1/5PtaseI-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/5PtaseI-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/5PtaseI-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/1/5PtaseI-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -8284.68 -8298.77
2 -8284.51 -8299.80
--------------------------------------
TOTAL -8284.59 -8299.41
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/5PtaseI-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/5PtaseI-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/1/5PtaseI-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} 0.968162 0.003112 0.867818 1.083542 0.967401 1308.78 1404.89 1.000
r(A<->C){all} 0.099686 0.000116 0.081406 0.122951 0.099177 1210.23 1222.68 1.000
r(A<->G){all} 0.268458 0.000426 0.230143 0.309299 0.268389 706.56 891.60 1.000
r(A<->T){all} 0.091114 0.000129 0.069036 0.113284 0.090581 786.80 798.83 1.000
r(C<->G){all} 0.096981 0.000134 0.075595 0.119950 0.096691 901.20 914.74 1.000
r(C<->T){all} 0.378941 0.000524 0.336056 0.425919 0.378619 768.32 853.43 1.001
r(G<->T){all} 0.064819 0.000110 0.044961 0.085004 0.064389 924.58 1180.20 1.001
pi(A){all} 0.283036 0.000083 0.265077 0.300604 0.283254 1191.74 1256.31 1.000
pi(C){all} 0.257115 0.000076 0.239213 0.273307 0.257200 1017.34 1136.05 1.002
pi(G){all} 0.227367 0.000071 0.210490 0.243386 0.227263 1036.11 1048.13 1.000
pi(T){all} 0.232482 0.000074 0.216235 0.249714 0.232278 837.05 1001.19 1.001
alpha{1,2} 0.219545 0.000490 0.177272 0.263333 0.217912 1226.54 1254.63 1.000
alpha{3} 2.757456 0.489018 1.531467 4.204025 2.660422 1287.61 1338.22 1.000
pinvar{all} 0.366366 0.001251 0.294696 0.430313 0.368564 1228.67 1245.91 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 -7464.802884
Model 2: PositiveSelection -7464.802933
Model 0: one-ratio -7578.010556
Model 3: discrete -7450.063675
Model 7: beta -7450.234033
Model 8: beta&w>1 -7450.234114
Model 0 vs 1 226.4153440000009
Model 2 vs 1 9.800000043469481E-5
Model 8 vs 7 1.6200000027311035E-4
