--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed May 09 12:45:09 WEST 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=
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/DNG_N2/NS2A_4/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_4/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/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6452.27 -6498.03
2 -6452.42 -6496.20
--------------------------------------
TOTAL -6452.34 -6497.49
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_4/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/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 9.336506 0.452743 8.038047 10.687740 9.301376 464.62 602.83 1.000
r(A<->C){all} 0.047047 0.000085 0.029947 0.065949 0.046691 679.13 740.11 1.000
r(A<->G){all} 0.214645 0.000326 0.178394 0.247501 0.214197 503.95 553.81 1.002
r(A<->T){all} 0.057231 0.000076 0.041865 0.075537 0.056888 791.97 899.13 1.000
r(C<->G){all} 0.051669 0.000109 0.031085 0.070905 0.051188 654.72 739.61 1.000
r(C<->T){all} 0.603610 0.000499 0.562566 0.647572 0.602958 369.49 481.63 1.002
r(G<->T){all} 0.025798 0.000068 0.009991 0.041353 0.025378 753.67 796.04 1.000
pi(A){all} 0.306025 0.000126 0.284311 0.327768 0.305865 594.29 684.45 1.000
pi(C){all} 0.215488 0.000092 0.197316 0.234215 0.215474 719.79 744.39 1.000
pi(G){all} 0.241226 0.000110 0.220255 0.260976 0.241085 860.57 921.65 1.000
pi(T){all} 0.237261 0.000098 0.217759 0.256455 0.236936 771.12 852.37 1.000
alpha{1,2} 0.390034 0.001514 0.320042 0.466318 0.387319 712.54 958.34 1.000
alpha{3} 4.174785 0.951195 2.517902 6.140725 4.048279 1040.30 1142.35 1.000
pinvar{all} 0.026314 0.000314 0.000006 0.060721 0.023523 1233.55 1312.99 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 -6133.329351
Model 2: PositiveSelection -6133.329351
Model 0: one-ratio -6149.747654
Model 3: discrete -6082.695715
Model 7: beta -6083.05543
Model 8: beta&w>1 -6083.055832
Model 0 vs 1 32.83660599999894
Model 2 vs 1 0.0
Model 8 vs 7 8.039999993343372E-4
