--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed Nov 08 10:14:39 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/ZikaADOPSresults/NS5/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/ZikaADOPSresults/NS5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/ZikaADOPSresults/NS5/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/ZikaADOPSresults/NS5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -10822.54 -10911.88
2 -10821.50 -10898.10
--------------------------------------
TOTAL -10821.89 -10911.18
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/ZikaADOPSresults/NS5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/ZikaADOPSresults/NS5/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/ZikaADOPSresults/NS5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.155229 0.002651 1.060746 1.261226 1.153351 902.26 993.88 1.001
r(A<->C){all} 0.029529 0.000020 0.020922 0.038110 0.029286 758.16 816.36 1.000
r(A<->G){all} 0.219318 0.000317 0.185821 0.254013 0.218515 210.25 288.47 1.002
r(A<->T){all} 0.032351 0.000030 0.021762 0.042626 0.032247 558.18 615.95 1.000
r(C<->G){all} 0.006054 0.000004 0.002344 0.009939 0.005919 780.96 781.29 1.000
r(C<->T){all} 0.690636 0.000436 0.649253 0.730652 0.691614 189.68 274.56 1.002
r(G<->T){all} 0.022112 0.000018 0.013546 0.030113 0.021911 789.62 808.13 1.000
pi(A){all} 0.279567 0.000062 0.264710 0.295412 0.279521 758.11 890.50 1.001
pi(C){all} 0.228286 0.000051 0.214933 0.242902 0.228134 779.29 933.40 1.001
pi(G){all} 0.297594 0.000066 0.282052 0.314153 0.297650 924.53 985.18 1.000
pi(T){all} 0.194553 0.000041 0.181853 0.206784 0.194518 856.13 895.46 1.001
alpha{1,2} 0.142173 0.000085 0.125022 0.160823 0.141804 862.32 1021.63 1.000
alpha{3} 5.201097 1.168830 3.299673 7.295986 5.084695 917.96 1144.41 1.000
pinvar{all} 0.251413 0.000776 0.198892 0.306758 0.252207 879.31 937.91 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 -10452.071124
Model 2: PositiveSelection -10452.071125
Model 0: one-ratio -10512.879866
Model 3: discrete -10442.852466
Model 7: beta -10444.785115
Model 8: beta&w>1 -10443.15373
Model 0 vs 1 121.61748399999851
Model 2 vs 1 2.0000006770715117E-6
Model 8 vs 7 3.262770000001183
