--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Oct 06 16:46:10 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=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_2/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_2/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/B2_A/Zika-NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -4400.59 -4478.35
2 -4408.29 -4474.69
--------------------------------------
TOTAL -4401.29 -4477.69
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_2/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/B2_A/Zika-NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 16.597211 2.478963 13.281510 19.474140 16.584730 356.34 387.59 1.001
r(A<->C){all} 0.026546 0.000053 0.013402 0.040819 0.025981 648.22 748.63 1.000
r(A<->G){all} 0.239647 0.001070 0.171298 0.299298 0.240774 159.86 192.33 1.002
r(A<->T){all} 0.031999 0.000072 0.016073 0.048187 0.031269 546.37 578.66 1.005
r(C<->G){all} 0.009031 0.000020 0.001253 0.017680 0.008285 540.18 665.27 1.000
r(C<->T){all} 0.674728 0.001412 0.605575 0.751826 0.673377 155.40 180.76 1.003
r(G<->T){all} 0.018049 0.000042 0.006223 0.030744 0.017317 559.50 626.88 1.000
pi(A){all} 0.289597 0.000177 0.264320 0.316037 0.289718 685.54 801.18 1.000
pi(C){all} 0.210774 0.000124 0.189478 0.232885 0.209951 773.15 867.98 1.000
pi(G){all} 0.298133 0.000181 0.272789 0.325806 0.298033 783.76 866.62 1.000
pi(T){all} 0.201496 0.000120 0.180706 0.223696 0.201413 793.24 847.52 1.000
alpha{1,2} 0.068706 0.000008 0.063635 0.074519 0.068549 534.84 592.78 1.000
alpha{3} 0.258719 0.000183 0.233074 0.284629 0.257990 396.63 480.58 1.003
pinvar{all} 0.381221 0.001193 0.307439 0.441371 0.382288 695.59 785.96 1.001
------------------------------------------------------------------------------------------------------
* 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 -3654.418098
Model 2: PositiveSelection -3654.418098
Model 0: one-ratio -3661.213426
Model 3: discrete -3647.050595
Model 7: beta -3647.77356
Model 8: beta&w>1 -3647.775811
Model 0 vs 1 13.590655999999399
Model 2 vs 1 0.0
Model 8 vs 7 0.004501999999774853
