--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 16:37:32 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/1/26-29-p-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/26-29-p-PA/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/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6459.17 -6478.37
2 -6458.33 -6475.80
--------------------------------------
TOTAL -6458.66 -6477.75
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/26-29-p-PA/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/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.395727 0.006669 1.245451 1.567078 1.392888 1417.92 1459.46 1.000
r(A<->C){all} 0.079864 0.000133 0.057824 0.102788 0.079302 1082.21 1163.84 1.000
r(A<->G){all} 0.237901 0.000491 0.194278 0.280108 0.237253 943.56 959.58 1.000
r(A<->T){all} 0.139145 0.000394 0.099716 0.175798 0.138606 861.41 906.85 1.000
r(C<->G){all} 0.056093 0.000065 0.041772 0.072933 0.055398 1165.38 1217.40 1.000
r(C<->T){all} 0.417615 0.000697 0.366654 0.470134 0.417678 843.37 861.39 1.000
r(G<->T){all} 0.069381 0.000143 0.047029 0.093248 0.068709 1031.95 1042.74 1.000
pi(A){all} 0.231037 0.000097 0.212153 0.249852 0.231068 1122.19 1160.88 1.000
pi(C){all} 0.294517 0.000097 0.276345 0.315336 0.294294 981.31 1117.82 1.000
pi(G){all} 0.264342 0.000098 0.246259 0.284971 0.264201 1146.48 1181.75 1.001
pi(T){all} 0.210103 0.000078 0.193861 0.228494 0.209995 1124.06 1132.98 1.001
alpha{1,2} 0.124657 0.000085 0.106656 0.142731 0.124103 1165.41 1314.09 1.000
alpha{3} 4.077650 0.827212 2.471403 5.978732 3.976993 759.08 1063.61 1.000
pinvar{all} 0.298656 0.000966 0.236553 0.357737 0.299561 1095.58 1265.72 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 -6059.250602
Model 2: PositiveSelection -6059.250602
Model 0: one-ratio -6101.198072
Model 3: discrete -6025.977293
Model 7: beta -6026.099343
Model 8: beta&w>1 -6026.10085
Model 0 vs 1 83.89494000000013
Model 2 vs 1 0.0
Model 8 vs 7 0.003013999999893713
