--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu Oct 05 23:37:12 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/B3_A/Zika-NS4B_1/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_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/B3_A/Zika-NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -3415.01 -3502.53
2 -3408.77 -3509.13
--------------------------------------
TOTAL -3409.46 -3508.44
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DATA/Zika/B3_A/Zika-NS4B_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/B3_A/Zika-NS4B_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} 15.101058 1.771210 12.543350 17.713610 15.053870 365.53 665.69 1.001
r(A<->C){all} 0.019764 0.000052 0.006825 0.033594 0.018879 252.24 295.90 1.000
r(A<->G){all} 0.182177 0.002173 0.108438 0.281746 0.172486 109.30 117.77 1.004
r(A<->T){all} 0.039531 0.000115 0.021553 0.061335 0.038335 231.55 337.67 1.003
r(C<->G){all} 0.003496 0.000009 0.000001 0.009521 0.002692 459.03 495.23 1.007
r(C<->T){all} 0.734913 0.003181 0.617848 0.828604 0.743729 103.77 114.71 1.006
r(G<->T){all} 0.020120 0.000052 0.006988 0.034403 0.019212 206.78 376.46 1.013
pi(A){all} 0.261451 0.000225 0.233679 0.291664 0.261674 838.56 933.51 1.000
pi(C){all} 0.252563 0.000199 0.223881 0.279417 0.252300 946.30 965.98 1.000
pi(G){all} 0.260868 0.000224 0.231771 0.290070 0.260537 828.43 859.92 1.000
pi(T){all} 0.225118 0.000177 0.199206 0.250935 0.224682 560.44 667.67 1.000
alpha{1,2} 0.073438 0.000010 0.067709 0.079962 0.073309 403.54 435.66 1.001
alpha{3} 0.282344 0.000418 0.243481 0.322988 0.280347 346.93 555.10 1.003
pinvar{all} 0.262039 0.001768 0.177148 0.341720 0.261534 443.51 503.98 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 -2917.05587
Model 2: PositiveSelection -2917.05587
Model 0: one-ratio -2947.643808
Model 3: discrete -2915.834153
Model 7: beta -2917.867125
Model 8: beta&w>1 -2917.867171
Model 0 vs 1 61.175875999999334
Model 2 vs 1 0.0
Model 8 vs 7 9.199999931297498E-5
