--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed Nov 02 14:53:29 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/14/Arl5-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/14/Arl5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/14/Arl5-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/14/Arl5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1790.96 -1809.44
2 -1790.54 -1807.98
--------------------------------------
TOTAL -1790.73 -1808.95
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/14/Arl5-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/14/Arl5-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/14/Arl5-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} 1.360324 0.022172 1.097790 1.672114 1.353018 1202.77 1276.11 1.000
r(A<->C){all} 0.099697 0.000529 0.057888 0.145736 0.097994 801.80 909.01 1.000
r(A<->G){all} 0.220806 0.001570 0.147453 0.300013 0.217351 743.81 774.80 1.001
r(A<->T){all} 0.017110 0.000296 0.000013 0.051406 0.011960 522.26 757.58 1.000
r(C<->G){all} 0.055933 0.000190 0.030834 0.084527 0.054713 1046.00 1050.16 1.000
r(C<->T){all} 0.572883 0.002536 0.472851 0.666363 0.573493 650.77 746.29 1.001
r(G<->T){all} 0.033571 0.000206 0.007509 0.061226 0.032221 995.13 1033.17 1.000
pi(A){all} 0.232541 0.000313 0.199698 0.268381 0.232665 933.09 993.88 1.000
pi(C){all} 0.286523 0.000303 0.250996 0.318808 0.286229 1212.98 1296.45 1.000
pi(G){all} 0.299230 0.000334 0.264494 0.336610 0.298622 1122.53 1160.52 1.000
pi(T){all} 0.181706 0.000218 0.153801 0.210788 0.181481 970.80 1099.16 1.000
alpha{1,2} 0.072469 0.000241 0.045571 0.104129 0.073167 958.46 1019.05 1.001
alpha{3} 3.430087 0.932108 1.761111 5.327696 3.287892 1203.73 1302.82 1.000
pinvar{all} 0.303055 0.002824 0.195675 0.400741 0.303969 1166.90 1331.58 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 -1592.168673
Model 2: PositiveSelection -1592.166905
Model 0: one-ratio -1592.281347
Model 3: discrete -1592.166905
Model 7: beta -1592.165772
Model 8: beta&w>1 -1592.200271
Model 0 vs 1 0.22534800000039468
Model 2 vs 1 0.003535999999712658
Model 8 vs 7 0.06899799999973766
