--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 22:04:22 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-PF/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/5PtaseI-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/5PtaseI-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/1/5PtaseI-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -8847.52 -8865.80
2 -8847.63 -8862.42
--------------------------------------
TOTAL -8847.57 -8865.14
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/5PtaseI-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/5PtaseI-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/1/5PtaseI-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} 0.887435 0.002468 0.793564 0.988190 0.886320 1399.09 1450.04 1.000
r(A<->C){all} 0.096964 0.000108 0.076210 0.115626 0.096577 1020.64 1117.10 1.000
r(A<->G){all} 0.257464 0.000376 0.216434 0.294368 0.257452 750.30 890.44 1.000
r(A<->T){all} 0.101488 0.000135 0.080163 0.125651 0.101215 1097.89 1117.57 1.000
r(C<->G){all} 0.091401 0.000109 0.070795 0.111304 0.091060 841.44 1018.91 1.001
r(C<->T){all} 0.385959 0.000487 0.341569 0.427906 0.385526 807.66 876.09 1.000
r(G<->T){all} 0.066724 0.000101 0.048357 0.086950 0.066391 988.92 1124.70 1.000
pi(A){all} 0.280879 0.000072 0.264816 0.297789 0.280890 1125.97 1143.40 1.000
pi(C){all} 0.257914 0.000070 0.241128 0.273970 0.257947 1152.15 1161.35 1.000
pi(G){all} 0.235088 0.000064 0.219931 0.250891 0.234953 754.16 1028.41 1.000
pi(T){all} 0.226119 0.000064 0.210238 0.241625 0.226067 933.41 1063.33 1.000
alpha{1,2} 0.230197 0.000527 0.185426 0.273018 0.228179 1132.01 1275.39 1.000
alpha{3} 3.178917 0.635412 1.795807 4.728869 3.067282 972.67 1148.74 1.000
pinvar{all} 0.374775 0.001089 0.310911 0.440002 0.376342 1137.29 1167.15 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 -8203.203783
Model 2: PositiveSelection -8203.203783
Model 0: one-ratio -8285.96666
Model 3: discrete -8186.471264
Model 7: beta -8186.591177
Model 8: beta&w>1 -8186.591304
Model 0 vs 1 165.52575399999841
Model 2 vs 1 0.0
Model 8 vs 7 2.539999986765906E-4
