--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 16 22:17:13 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_2_2/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_2_2/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_2_2/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -16474.34 -16517.23
2 -16470.66 -16524.86
--------------------------------------
TOTAL -16471.33 -16524.17
--------------------------------------
Model parameter summaries over the runs sampled in files
"/data/repeat/ns3_2_2/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_2_2/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_2_2/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 9.099681 0.194060 8.323410 10.026560 9.075611 383.12 561.46 1.001
r(A<->C){all} 0.034636 0.000014 0.026914 0.041310 0.034574 687.82 724.85 1.000
r(A<->G){all} 0.205783 0.000123 0.183685 0.227445 0.205538 317.35 400.45 1.000
r(A<->T){all} 0.040326 0.000016 0.032367 0.048120 0.040322 783.33 865.44 1.001
r(C<->G){all} 0.015969 0.000012 0.009208 0.022746 0.015861 780.91 830.58 1.000
r(C<->T){all} 0.681059 0.000183 0.654150 0.706759 0.681408 307.00 381.33 1.000
r(G<->T){all} 0.022228 0.000017 0.014546 0.030739 0.022118 616.67 653.64 1.000
pi(A){all} 0.360611 0.000060 0.345979 0.375990 0.360551 799.09 825.63 1.001
pi(C){all} 0.212207 0.000040 0.200288 0.224631 0.212081 615.22 706.87 1.000
pi(G){all} 0.227403 0.000044 0.213735 0.239334 0.227378 546.86 606.56 1.000
pi(T){all} 0.199779 0.000036 0.188522 0.211559 0.199575 763.11 850.04 1.001
alpha{1,2} 0.156759 0.000041 0.144420 0.168852 0.156553 1178.05 1282.77 1.001
alpha{3} 6.347302 0.905175 4.699067 8.225644 6.297386 1314.88 1407.94 1.000
pinvar{all} 0.119365 0.000283 0.088198 0.152563 0.119169 1329.32 1343.77 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 -15870.135482
Model 2: PositiveSelection -15870.135482
Model 0: one-ratio -15944.128229
Model 3: discrete -15702.282049
Model 7: beta -15706.727427
Model 8: beta&w>1 -15706.19979
Model 0 vs 1 147.98549400000047
Model 2 vs 1 0.0
Model 8 vs 7 1.0552739999984624
