--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sun Oct 08 03:47:30 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/B3_A/Zika-NS4B_5/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_5/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/B3_A/Zika-NS4B_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -3609.72 -3705.56
2 -3613.01 -3706.65
--------------------------------------
TOTAL -3610.38 -3706.25
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_5/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/B3_A/Zika-NS4B_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 15.264623 2.282281 12.350370 18.298370 15.248630 528.91 572.09 1.000
r(A<->C){all} 0.023677 0.000056 0.010464 0.038767 0.022949 644.03 740.61 1.001
r(A<->G){all} 0.242827 0.001936 0.148156 0.325439 0.244216 193.16 221.31 1.000
r(A<->T){all} 0.059445 0.000162 0.035405 0.083768 0.058813 476.21 477.24 1.000
r(C<->G){all} 0.012366 0.000032 0.003160 0.024003 0.011492 381.21 483.88 1.000
r(C<->T){all} 0.632217 0.002760 0.534817 0.742530 0.629648 183.95 215.00 1.000
r(G<->T){all} 0.029469 0.000083 0.013396 0.048432 0.028410 501.36 526.26 1.000
pi(A){all} 0.263622 0.000224 0.233116 0.291366 0.263681 732.51 849.29 1.000
pi(C){all} 0.250307 0.000186 0.224573 0.276967 0.250425 918.74 921.18 1.000
pi(G){all} 0.259313 0.000215 0.231060 0.287604 0.259242 650.75 796.15 1.000
pi(T){all} 0.226758 0.000181 0.199632 0.251982 0.226721 832.25 840.18 1.000
alpha{1,2} 0.076450 0.000012 0.069776 0.083272 0.076277 829.98 847.73 1.000
alpha{3} 0.305445 0.000587 0.263908 0.354637 0.302732 565.99 601.20 1.000
pinvar{all} 0.292154 0.001639 0.211599 0.366891 0.293969 667.64 709.60 1.001
------------------------------------------------------------------------------------------------------
* 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 -3235.201478
Model 2: PositiveSelection -3235.176513
Model 0: one-ratio -3277.003946
Model 3: discrete -3234.226796
Model 7: beta -3235.963243
Model 8: beta&w>1 -3235.963784
Model 0 vs 1 83.60493599999973
Model 2 vs 1 0.04993000000013126
Model 8 vs 7 0.001081999999769323
