--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sun Oct 08 06:02:51 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/DATA/Zika/B2_A/Zika-NS1_4/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_4/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/DATA/Zika/B2_A/Zika-NS1_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -4251.85 -4338.35
2 -4251.76 -4335.80
--------------------------------------
TOTAL -4251.80 -4337.73
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_4/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/DATA/Zika/B2_A/Zika-NS1_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 16.204429 2.763839 12.793460 19.258120 16.249460 177.22 180.94 1.022
r(A<->C){all} 0.031193 0.000076 0.016078 0.049308 0.030296 198.60 214.43 1.005
r(A<->G){all} 0.210437 0.002583 0.096297 0.294179 0.218719 57.20 68.60 1.046
r(A<->T){all} 0.031975 0.000089 0.015497 0.051734 0.031330 148.51 179.81 1.012
r(C<->G){all} 0.007503 0.000017 0.000916 0.015475 0.006895 660.84 722.23 1.000
r(C<->T){all} 0.694252 0.003821 0.593376 0.836197 0.682576 51.17 63.36 1.048
r(G<->T){all} 0.024640 0.000061 0.009547 0.039124 0.023998 238.79 248.35 1.011
pi(A){all} 0.286575 0.000185 0.259524 0.311500 0.286354 675.91 795.45 1.005
pi(C){all} 0.210384 0.000121 0.189323 0.231898 0.209933 740.98 798.58 1.002
pi(G){all} 0.298313 0.000178 0.271243 0.323495 0.297991 547.88 694.98 1.000
pi(T){all} 0.204727 0.000118 0.182902 0.225058 0.204593 942.11 961.54 1.000
alpha{1,2} 0.069273 0.000011 0.063215 0.075482 0.069039 146.69 177.51 1.018
alpha{3} 0.252505 0.000182 0.226996 0.279545 0.251704 351.32 429.96 1.000
pinvar{all} 0.409235 0.001561 0.328038 0.483098 0.411992 114.94 133.66 1.020
------------------------------------------------------------------------------------------------------
* 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 -3497.189929
Model 2: PositiveSelection -3497.190052
Model 0: one-ratio -3501.803461
Model 3: discrete -3489.842715
Model 7: beta -3490.529667
Model 8: beta&w>1 -3490.530396
Model 0 vs 1 9.2270639999997
Model 2 vs 1 2.459999996062834E-4
Model 8 vs 7 0.0014580000006390037
