--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Oct 28 06:00:26 WEST 2017
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=MUSCLE
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=/usr/bin/
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb
tcoffee.bin=t_coffee
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/Ebola_B1_2/VP40/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/Ebola_B1_2/VP40/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Ebola_B1_2/VP40/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/Ebola_B1_2/VP40/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6554.53 -6601.94
2 -6550.76 -6599.98
--------------------------------------
TOTAL -6551.43 -6601.38
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/Ebola_B1_2/VP40/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Ebola_B1_2/VP40/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/Ebola_B1_2/VP40/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 4.570179 0.106992 3.942134 5.198495 4.550034 650.73 780.96 1.000
r(A<->C){all} 0.130904 0.000231 0.103766 0.163054 0.130414 1011.18 1032.10 1.002
r(A<->G){all} 0.383981 0.000838 0.329177 0.440463 0.383506 563.09 694.39 1.000
r(A<->T){all} 0.057341 0.000182 0.031586 0.082838 0.056619 638.04 667.94 1.001
r(C<->G){all} 0.007950 0.000047 0.000001 0.021419 0.006165 837.57 856.76 1.000
r(C<->T){all} 0.357009 0.000782 0.301381 0.411328 0.356658 615.56 690.22 1.000
r(G<->T){all} 0.062815 0.000188 0.038233 0.090299 0.062217 700.35 741.38 1.000
pi(A){all} 0.270731 0.000076 0.254692 0.288760 0.270501 905.75 919.35 1.001
pi(C){all} 0.270998 0.000077 0.254142 0.288079 0.270995 910.06 935.40 1.000
pi(G){all} 0.226358 0.000071 0.210334 0.243713 0.226414 1005.55 1076.59 1.000
pi(T){all} 0.231912 0.000070 0.215531 0.247979 0.231723 1009.89 1112.30 1.000
alpha{1,2} 0.165895 0.000126 0.143891 0.187268 0.165103 1033.11 1091.52 1.000
alpha{3} 4.140493 0.855780 2.522022 5.948563 4.022639 1116.81 1174.84 1.000
pinvar{all} 0.031809 0.000332 0.000116 0.066286 0.029833 1163.53 1272.61 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 -4996.181233
Model 2: PositiveSelection -4996.181233
Model 0: one-ratio -5066.591126
Model 3: discrete -4958.357556
Model 7: beta -4961.765258
Model 8: beta&w>1 -4961.765895
Model 0 vs 1 140.81978600000002
Model 2 vs 1 0.0
Model 8 vs 7 0.001273999998375075
