--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Sep 30 16:54:04 WEST 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=/usr/bin/
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb
tcoffee.bin=t_coffee
mrbayes.dir=
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-M/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-M/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-M/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/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-M/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1473.01 -1537.17
2 -1477.80 -1553.40
--------------------------------------
TOTAL -1473.70 -1552.70
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-M/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-M/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/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-M/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 15.769697 1.722057 13.105090 18.212610 15.733120 773.49 1013.24 1.000
r(A<->C){all} 0.038430 0.000179 0.014557 0.064083 0.036892 509.63 532.50 1.000
r(A<->G){all} 0.159916 0.001654 0.083393 0.240522 0.155462 268.59 273.48 1.001
r(A<->T){all} 0.057308 0.000372 0.022325 0.094281 0.054990 457.14 529.32 1.000
r(C<->G){all} 0.031517 0.000166 0.009225 0.056913 0.029861 624.50 654.68 1.003
r(C<->T){all} 0.662931 0.003222 0.551174 0.774382 0.665339 256.58 257.26 1.000
r(G<->T){all} 0.049898 0.000370 0.015740 0.086891 0.047543 422.72 497.18 1.000
pi(A){all} 0.269931 0.000754 0.215175 0.320818 0.269214 632.69 725.80 1.004
pi(C){all} 0.279514 0.000607 0.232070 0.328321 0.279575 578.05 662.13 1.001
pi(G){all} 0.234634 0.000647 0.186939 0.284106 0.233310 761.46 774.07 1.000
pi(T){all} 0.215921 0.000465 0.174092 0.256453 0.215094 888.98 931.98 1.000
alpha{1,2} 0.091815 0.000033 0.081070 0.103136 0.091334 621.75 754.25 1.000
alpha{3} 0.356685 0.001297 0.297301 0.429285 0.352270 922.53 939.47 1.001
pinvar{all} 0.111212 0.003561 0.000106 0.214618 0.108030 841.49 1000.73 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 -1065.490048
Model 2: PositiveSelection -1065.489532
Model 0: one-ratio -1065.489532
Model 3: discrete -1065.489532
Model 7: beta -1065.675108
Model 8: beta&w>1 -1065.675727
Model 0 vs 1 0.0010319999996681872
Model 2 vs 1 0.0010319999996681872
Model 8 vs 7 0.0012380000002849556
