--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed Nov 08 16:38:18 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=
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/ZikaORes/NS2A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/ZikaORes/NS2A/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/ZikaORes/NS2A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -2928.82 -3005.87
2 -2928.49 -3005.96
--------------------------------------
TOTAL -2928.64 -3005.92
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/ZikaORes/NS2A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/ZikaORes/NS2A/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/ZikaORes/NS2A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.618791 0.036579 1.282504 1.998519 1.597028 738.28 738.42 1.000
r(A<->C){all} 0.033190 0.000110 0.014455 0.054977 0.032106 511.34 630.82 1.001
r(A<->G){all} 0.203858 0.001244 0.137675 0.272022 0.201560 377.94 445.30 1.000
r(A<->T){all} 0.044198 0.000156 0.020840 0.068162 0.043284 625.77 649.02 1.000
r(C<->G){all} 0.010708 0.000023 0.002479 0.019935 0.010122 812.25 891.70 1.002
r(C<->T){all} 0.690876 0.001874 0.604870 0.772324 0.691413 372.41 441.60 1.000
r(G<->T){all} 0.017170 0.000040 0.005967 0.029190 0.016525 670.31 757.34 1.000
pi(A){all} 0.211127 0.000198 0.184542 0.238751 0.210834 806.95 878.54 1.000
pi(C){all} 0.253950 0.000204 0.227373 0.283189 0.254195 705.29 885.93 1.000
pi(G){all} 0.279953 0.000257 0.248456 0.310956 0.279544 880.42 971.24 1.000
pi(T){all} 0.254970 0.000202 0.225655 0.282066 0.254959 773.78 897.48 1.000
alpha{1,2} 0.201665 0.000598 0.159522 0.250920 0.199658 820.50 963.60 1.000
alpha{3} 2.768955 0.645748 1.440741 4.394516 2.656267 1090.24 1147.30 1.000
pinvar{all} 0.178732 0.002585 0.074860 0.271100 0.181921 940.06 974.70 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 -2767.787453
Model 2: PositiveSelection -2767.787454
Model 0: one-ratio -2767.962307
Model 3: discrete -2761.921638
Model 7: beta -2762.607956
Model 8: beta&w>1 -2762.608612
Model 0 vs 1 0.3497079999997368
Model 2 vs 1 1.99999976757681E-6
Model 8 vs 7 0.0013120000003254972
