--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Sep 30 21:18:16 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-NS4A/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-NS4A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-NS4A/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-NS4A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1770.42 -1847.99
2 -1781.33 -1844.87
--------------------------------------
TOTAL -1771.11 -1847.34
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-NS4A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/Batch_1_ADOPS/Zika-NS4A/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-NS4A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 13.276222 1.477160 10.999750 15.664800 13.249460 996.68 1024.76 1.000
r(A<->C){all} 0.032708 0.000185 0.011352 0.060066 0.030292 427.16 450.40 1.000
r(A<->G){all} 0.125645 0.002135 0.054468 0.226234 0.115532 221.49 257.69 1.000
r(A<->T){all} 0.019681 0.000116 0.002481 0.040766 0.017953 342.23 409.88 1.000
r(C<->G){all} 0.008553 0.000027 0.000598 0.018280 0.007590 630.20 721.05 1.002
r(C<->T){all} 0.805026 0.003663 0.669135 0.899584 0.815784 217.40 260.09 1.000
r(G<->T){all} 0.008387 0.000033 0.000009 0.019281 0.007124 622.20 703.86 1.000
pi(A){all} 0.230422 0.000384 0.193433 0.269012 0.229969 821.78 848.36 1.002
pi(C){all} 0.236246 0.000330 0.202710 0.272727 0.236391 924.96 1022.55 1.001
pi(G){all} 0.303681 0.000472 0.264109 0.348127 0.303157 812.18 842.32 1.000
pi(T){all} 0.229651 0.000338 0.194477 0.265779 0.229456 820.40 847.38 1.000
alpha{1,2} 0.086537 0.000035 0.074815 0.097720 0.086130 808.99 973.05 1.000
alpha{3} 0.341138 0.010658 0.235984 0.608174 0.306821 213.73 328.97 1.000
pinvar{all} 0.335177 0.002892 0.234339 0.443935 0.334452 672.18 847.91 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 -1430.147849
Model 2: PositiveSelection -1430.147849
Model 0: one-ratio -1430.877046
Model 3: discrete -1428.604927
Model 7: beta -1428.679144
Model 8: beta&w>1 -1428.679412
Model 0 vs 1 1.4583940000002258
Model 2 vs 1 0.0
Model 8 vs 7 5.360000000109721E-4
