--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Jan 19 04:18:02 GMT 2019
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=/opt/mrbayes_3.2.2/src
tcoffee.dir=
tcoffee.minScore=3
input.fasta=
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p":
(Use the harmonic mean for Bayes factor comparisons of models)
(Values are saved to the file /data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -7418.45 -7456.04
2 -7418.08 -7457.16
--------------------------------------
TOTAL -7418.25 -7456.75
--------------------------------------
Model parameter summaries over the runs sampled in files
"/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/A_NS4B_4/Muscle/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 "/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 7.590823 0.214131 6.706226 8.490758 7.584121 868.41 908.65 1.000
r(A<->C){all} 0.036110 0.000036 0.024139 0.047987 0.035873 614.37 757.38 1.000
r(A<->G){all} 0.221680 0.000318 0.188398 0.257473 0.221338 382.68 504.75 1.000
r(A<->T){all} 0.054762 0.000051 0.041082 0.068839 0.054573 718.27 771.60 1.000
r(C<->G){all} 0.041638 0.000052 0.027495 0.055087 0.041212 865.25 907.53 1.000
r(C<->T){all} 0.620749 0.000478 0.576920 0.661524 0.620833 410.42 510.14 1.000
r(G<->T){all} 0.025060 0.000039 0.013636 0.037554 0.024813 586.14 669.90 1.001
pi(A){all} 0.328907 0.000154 0.306444 0.355033 0.328711 861.38 901.38 1.000
pi(C){all} 0.236693 0.000107 0.215692 0.256676 0.236531 756.15 827.90 1.000
pi(G){all} 0.214890 0.000118 0.194189 0.236089 0.214773 704.42 746.15 1.001
pi(T){all} 0.219510 0.000102 0.199966 0.239241 0.219327 617.88 661.69 1.000
alpha{1,2} 0.208312 0.000229 0.181524 0.238773 0.206892 1257.04 1335.81 1.000
alpha{3} 4.676802 0.762977 3.075306 6.410978 4.600007 1425.82 1463.41 1.000
pinvar{all} 0.125559 0.000726 0.073897 0.177822 0.124561 1282.91 1356.19 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 -6939.894242
Model 2: PositiveSelection -6939.894242
Model 0: one-ratio -6982.542395
Model 3: discrete -6873.849457
Model 7: beta -6877.893161
Model 8: beta&w>1 -6877.895608
Model 0 vs 1 85.29630600000019
Model 2 vs 1 0.0
Model 8 vs 7 0.004893999999694643
