--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Tue Nov 07 12:06:05 WET 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=
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/ADOPS1/Zikaomegamapresults/NS3/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/Zikaomegamapresults/NS3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Zikaomegamapresults/NS3/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/ADOPS1/Zikaomegamapresults/NS3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6667.04 -6721.40
2 -6667.36 -6716.36
--------------------------------------
TOTAL -6667.19 -6720.72
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/Zikaomegamapresults/NS3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Zikaomegamapresults/NS3/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/ADOPS1/Zikaomegamapresults/NS3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.986945 0.003234 0.877329 1.093764 0.984761 1121.56 1271.91 1.000
r(A<->C){all} 0.027642 0.000033 0.016475 0.038272 0.027280 817.57 937.67 1.000
r(A<->G){all} 0.185669 0.000391 0.149932 0.226149 0.184579 510.94 557.00 1.000
r(A<->T){all} 0.039323 0.000053 0.026448 0.054140 0.038636 914.55 971.25 1.000
r(C<->G){all} 0.020315 0.000026 0.010691 0.030139 0.019927 902.89 928.97 1.001
r(C<->T){all} 0.685568 0.000624 0.636590 0.733401 0.686288 463.45 510.58 1.000
r(G<->T){all} 0.041484 0.000059 0.027341 0.056635 0.040790 740.08 793.43 1.000
pi(A){all} 0.280754 0.000097 0.261049 0.299069 0.280520 930.55 1065.88 1.000
pi(C){all} 0.229590 0.000076 0.213709 0.247104 0.229665 1004.18 1084.28 1.000
pi(G){all} 0.280983 0.000095 0.263454 0.300996 0.280864 906.98 1076.48 1.000
pi(T){all} 0.208673 0.000070 0.192853 0.225612 0.208679 1046.40 1147.66 1.000
alpha{1,2} 0.136515 0.000137 0.116085 0.160284 0.136054 998.60 1113.86 1.000
alpha{3} 4.522827 1.051938 2.724199 6.586011 4.408111 1176.54 1338.77 1.000
pinvar{all} 0.258966 0.001324 0.186359 0.325988 0.260131 1058.20 1133.02 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 -6403.791453
Model 2: PositiveSelection -6403.791454
Model 0: one-ratio -6421.477267
Model 3: discrete -6397.236881
Model 7: beta -6397.328339
Model 8: beta&w>1 -6397.328595
Model 0 vs 1 35.37162800000078
Model 2 vs 1 2.0000006770715117E-6
Model 8 vs 7 5.120000005263137E-4
