--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu Feb 18 16:59:54 WET 2016
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/B4_A/Zika-NS5_4/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_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/B4_A/Zika-NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -9092.17 -9173.46
2 -9087.97 -9190.61
--------------------------------------
TOTAL -9088.65 -9189.91
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B4_A/Zika-NS5_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/B4_A/Zika-NS5_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} 1.082852 0.003223 0.973582 1.197589 1.080876 459.88 477.61 1.000
r(A<->C){all} 0.022532 0.000018 0.014307 0.031134 0.022322 814.98 908.29 1.000
r(A<->G){all} 0.219084 0.000443 0.179541 0.259466 0.217997 413.71 444.60 1.000
r(A<->T){all} 0.027275 0.000030 0.017051 0.037932 0.026899 733.37 739.62 1.002
r(C<->G){all} 0.006560 0.000006 0.002064 0.011187 0.006269 682.25 705.63 1.000
r(C<->T){all} 0.704344 0.000579 0.660163 0.752669 0.705359 329.62 370.40 1.000
r(G<->T){all} 0.020206 0.000020 0.011900 0.029312 0.019950 543.81 643.98 1.001
pi(A){all} 0.279823 0.000063 0.264921 0.295600 0.279672 844.22 898.85 1.000
pi(C){all} 0.227426 0.000052 0.213801 0.241997 0.227649 654.10 709.96 1.000
pi(G){all} 0.295871 0.000066 0.280237 0.311779 0.295871 886.94 890.36 1.003
pi(T){all} 0.196880 0.000046 0.183018 0.210027 0.196781 807.42 888.73 1.000
alpha{1,2} 0.109801 0.000078 0.093189 0.127740 0.109636 1111.52 1175.65 1.001
alpha{3} 4.898783 1.062486 3.077460 6.942204 4.789856 1116.79 1204.92 1.000
pinvar{all} 0.266643 0.000915 0.206271 0.325327 0.267805 927.39 985.31 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 -8491.066751
Model 2: PositiveSelection -8491.066747
Model 0: one-ratio -8538.702434
Model 3: discrete -8487.233605
Model 7: beta -8487.588366
Model 8: beta&w>1 -8487.590316
Model 0 vs 1 95.27136600000085
Model 2 vs 1 7.99999907030724E-6
Model 8 vs 7 0.003899999999703141
