--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu Nov 10 12:29:17 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/181/CG7083-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/181/CG7083-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/181/CG7083-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/181/CG7083-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -5209.04 -5227.43
2 -5208.88 -5223.93
--------------------------------------
TOTAL -5208.96 -5226.76
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/181/CG7083-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/181/CG7083-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/181/CG7083-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} 1.702692 0.011701 1.493753 1.908819 1.698187 1177.90 1286.97 1.000
r(A<->C){all} 0.083008 0.000190 0.057570 0.110335 0.082458 1016.53 1022.05 1.000
r(A<->G){all} 0.255587 0.000618 0.205051 0.302150 0.254780 769.63 817.01 1.000
r(A<->T){all} 0.126897 0.000525 0.083678 0.172338 0.125318 1091.88 1140.00 1.000
r(C<->G){all} 0.040637 0.000059 0.026090 0.055873 0.040365 986.18 1022.87 1.001
r(C<->T){all} 0.413254 0.000850 0.355632 0.469911 0.412581 643.63 738.07 1.000
r(G<->T){all} 0.080617 0.000180 0.055062 0.107431 0.080126 1019.36 1100.24 1.000
pi(A){all} 0.205867 0.000113 0.185532 0.226821 0.205894 942.29 1005.29 1.000
pi(C){all} 0.315219 0.000139 0.291760 0.337726 0.315189 1206.79 1207.91 1.001
pi(G){all} 0.263560 0.000126 0.241722 0.285108 0.263421 971.30 1065.10 1.000
pi(T){all} 0.215353 0.000097 0.196484 0.234716 0.215109 956.67 978.45 1.002
alpha{1,2} 0.103333 0.000061 0.088273 0.118599 0.103078 1259.78 1338.73 1.000
alpha{3} 3.979536 0.818128 2.371988 5.788409 3.869927 1501.00 1501.00 1.001
pinvar{all} 0.256527 0.001133 0.189781 0.320693 0.257440 1358.34 1385.91 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 -4801.915611
Model 2: PositiveSelection -4801.915628
Model 0: one-ratio -4812.778724
Model 3: discrete -4784.669563
Model 7: beta -4784.683497
Model 8: beta&w>1 -4784.686737
Model 0 vs 1 21.72622599999886
Model 2 vs 1 3.3999998777289875E-5
Model 8 vs 7 0.006480000000010477
