--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Tue Nov 13 23:59:33 GMT 2018
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/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_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/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -15023.98 -15061.84
2 -15025.14 -15063.44
--------------------------------------
TOTAL -15024.40 -15062.93
--------------------------------------
Model parameter summaries over the runs sampled in files
"/data/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_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/repeat/ns3_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} 8.142768 0.178056 7.312768 8.917170 8.134761 508.04 750.36 1.000
r(A<->C){all} 0.036531 0.000017 0.028414 0.044292 0.036486 729.96 854.62 1.000
r(A<->G){all} 0.199935 0.000145 0.176875 0.224298 0.199886 378.33 429.99 1.003
r(A<->T){all} 0.040589 0.000020 0.031458 0.048652 0.040562 502.64 689.70 1.000
r(C<->G){all} 0.019217 0.000014 0.012086 0.026592 0.019035 856.59 906.08 1.000
r(C<->T){all} 0.684672 0.000215 0.656985 0.714113 0.684637 428.79 441.27 1.002
r(G<->T){all} 0.019055 0.000017 0.011421 0.027215 0.018816 614.70 687.90 1.000
pi(A){all} 0.356276 0.000066 0.339888 0.371882 0.356212 638.40 744.26 1.000
pi(C){all} 0.219145 0.000044 0.206394 0.232256 0.219122 517.30 542.83 1.000
pi(G){all} 0.228976 0.000049 0.215660 0.243032 0.228948 561.05 623.81 1.001
pi(T){all} 0.195603 0.000037 0.184025 0.208137 0.195576 558.82 663.26 1.001
alpha{1,2} 0.161910 0.000051 0.147876 0.175571 0.161671 1094.53 1252.79 1.000
alpha{3} 5.358050 0.676307 3.913713 7.067442 5.279592 1371.88 1436.44 1.000
pinvar{all} 0.115719 0.000300 0.082447 0.150216 0.115379 1082.58 1171.53 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 -14400.462733
Model 2: PositiveSelection -14400.462734
Model 0: one-ratio -14440.654751
Model 3: discrete -14263.518451
Model 7: beta -14266.551944
Model 8: beta&w>1 -14266.558115
Model 0 vs 1 80.38403599999947
Model 2 vs 1 2.0000006770715117E-6
Model 8 vs 7 0.01234199999817065
