--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Mon Nov 06 17:35:10 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/E/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/Zikaomegamapresults/E/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Zikaomegamapresults/E/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/E/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -5848.52 -5915.94
2 -5845.71 -5905.07
--------------------------------------
TOTAL -5846.34 -5915.25
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/Zikaomegamapresults/E/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Zikaomegamapresults/E/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/E/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.133307 0.005177 0.994493 1.278667 1.132369 861.87 966.70 1.000
r(A<->C){all} 0.030545 0.000044 0.018127 0.043413 0.030059 858.95 871.15 1.000
r(A<->G){all} 0.163993 0.000468 0.120537 0.203859 0.162416 326.95 383.81 1.002
r(A<->T){all} 0.034608 0.000057 0.021110 0.049862 0.034148 668.60 716.70 1.000
r(C<->G){all} 0.021679 0.000031 0.011621 0.032941 0.021169 704.21 821.66 1.000
r(C<->T){all} 0.720793 0.000783 0.665378 0.773396 0.722229 302.12 334.85 1.002
r(G<->T){all} 0.028383 0.000042 0.016420 0.041449 0.028098 745.26 748.22 1.000
pi(A){all} 0.262595 0.000109 0.240664 0.281603 0.262395 812.25 909.88 1.002
pi(C){all} 0.232886 0.000091 0.215850 0.252868 0.232893 944.55 1118.86 1.000
pi(G){all} 0.280738 0.000119 0.258213 0.300637 0.280894 709.23 909.74 1.000
pi(T){all} 0.223781 0.000086 0.206455 0.242775 0.223708 980.33 1018.73 1.000
alpha{1,2} 0.164407 0.000210 0.138357 0.195143 0.163339 1081.91 1176.46 1.000
alpha{3} 3.755622 0.926429 2.123162 5.680947 3.645178 1427.04 1464.02 1.002
pinvar{all} 0.247361 0.001527 0.172606 0.324963 0.247737 866.32 993.96 1.002
------------------------------------------------------------------------------------------------------
* 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 -5514.964793
Model 2: PositiveSelection -5515.564412
Model 0: one-ratio -5515.564658
Model 3: discrete -5509.224666
Model 7: beta -5509.941309
Model 8: beta&w>1 -5509.946172
Model 0 vs 1 1.1997300000002724
Model 2 vs 1 1.1992379999992409
Model 8 vs 7 0.009726000000227941
