--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Nov 08 16:38:18 WET 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=
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb_adops
tcoffee.bin=t_coffee_ADOPS
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/ZikaORes/NS2A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/ZikaORes/NS2A/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/ADOPS1/ZikaORes/NS2A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -2928.82         -3005.87
2      -2928.49         -3005.96
--------------------------------------
TOTAL    -2928.64         -3005.92
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/ZikaORes/NS2A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/ZikaORes/NS2A/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/ADOPS1/ZikaORes/NS2A/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.618791    0.036579    1.282504    1.998519    1.597028    738.28    738.42    1.000
r(A<->C){all}   0.033190    0.000110    0.014455    0.054977    0.032106    511.34    630.82    1.001
r(A<->G){all}   0.203858    0.001244    0.137675    0.272022    0.201560    377.94    445.30    1.000
r(A<->T){all}   0.044198    0.000156    0.020840    0.068162    0.043284    625.77    649.02    1.000
r(C<->G){all}   0.010708    0.000023    0.002479    0.019935    0.010122    812.25    891.70    1.002
r(C<->T){all}   0.690876    0.001874    0.604870    0.772324    0.691413    372.41    441.60    1.000
r(G<->T){all}   0.017170    0.000040    0.005967    0.029190    0.016525    670.31    757.34    1.000
pi(A){all}      0.211127    0.000198    0.184542    0.238751    0.210834    806.95    878.54    1.000
pi(C){all}      0.253950    0.000204    0.227373    0.283189    0.254195    705.29    885.93    1.000
pi(G){all}      0.279953    0.000257    0.248456    0.310956    0.279544    880.42    971.24    1.000
pi(T){all}      0.254970    0.000202    0.225655    0.282066    0.254959    773.78    897.48    1.000
alpha{1,2}      0.201665    0.000598    0.159522    0.250920    0.199658    820.50    963.60    1.000
alpha{3}        2.768955    0.645748    1.440741    4.394516    2.656267   1090.24   1147.30    1.000
pinvar{all}     0.178732    0.002585    0.074860    0.271100    0.181921    940.06    974.70    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	-2767.787453
Model 2: PositiveSelection	-2767.787454
Model 0: one-ratio	-2767.962307
Model 3: discrete	-2761.921638
Model 7: beta	-2762.607956
Model 8: beta&w>1	-2762.608612


Model 0 vs 1	0.3497079999997368

Model 2 vs 1	1.99999976757681E-6

Model 8 vs 7	0.0013120000003254972