--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu Oct 05 23:13:37 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_1/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_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_1/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_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -4271.55 -4351.50
2 -4231.87 -4318.87
--------------------------------------
TOTAL -4232.56 -4350.81
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B2_A/Zika-NS1_1/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_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 14.769727 2.145047 11.862030 17.608370 14.774270 81.84 409.42 1.099
r(A<->C){all} 0.012013 0.000139 0.000018 0.031625 0.007175 116.60 212.98 2.887
r(A<->G){all} 0.082452 0.006760 0.004091 0.219470 0.063264 47.32 78.74 2.963
r(A<->T){all} 0.013605 0.000162 0.000686 0.035950 0.005918 147.50 198.28 2.629
r(C<->G){all} 0.003862 0.000018 0.000030 0.012404 0.001571 303.35 434.38 1.737
r(C<->T){all} 0.877249 0.013642 0.692226 0.991926 0.979559 44.11 76.24 3.418
r(G<->T){all} 0.010819 0.000102 0.000493 0.029233 0.005115 74.42 163.35 2.410
pi(A){all} 0.294127 0.000198 0.268270 0.322398 0.293968 556.51 715.78 1.069
pi(C){all} 0.212284 0.000138 0.189922 0.235044 0.212283 214.77 536.77 1.034
pi(G){all} 0.292090 0.000181 0.266072 0.318648 0.291899 281.80 556.00 1.032
pi(T){all} 0.201498 0.000135 0.179705 0.224763 0.201183 221.00 633.56 1.090
alpha{1,2} 0.066671 0.000029 0.056684 0.076392 0.066585 202.78 264.51 1.985
alpha{3} 0.407146 0.023621 0.228882 0.601040 0.471867 121.07 253.20 10.499
pinvar{all} 0.333347 0.003594 0.234196 0.443611 0.330952 348.12 723.05 2.187
------------------------------------------------------------------------------------------------------
* 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 -3631.898993
Model 2: PositiveSelection -3631.898992
Model 0: one-ratio -3637.596052
Model 3: discrete -3629.469799
Model 7: beta -3629.644731
Model 8: beta&w>1 -3629.644885
Model 0 vs 1 11.394118000000162
Model 2 vs 1 1.99999976757681E-6
Model 8 vs 7 3.080000005866168E-4
