--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Jan 19 04:18:02 GMT 2019
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=/opt/mrbayes_3.2.2/src
tcoffee.dir=
tcoffee.minScore=3
input.fasta=
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p":
(Use the harmonic mean for Bayes factor comparisons of models)

(Values are saved to the file /data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -7418.45         -7456.04
2      -7418.08         -7457.16
--------------------------------------
TOTAL    -7418.25         -7456.75
--------------------------------------


Model parameter summaries over the runs sampled in files
"/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/A_NS4B_4/Muscle/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 "/data/A_NS4B_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         7.590823    0.214131    6.706226    8.490758    7.584121    868.41    908.65    1.000
r(A<->C){all}   0.036110    0.000036    0.024139    0.047987    0.035873    614.37    757.38    1.000
r(A<->G){all}   0.221680    0.000318    0.188398    0.257473    0.221338    382.68    504.75    1.000
r(A<->T){all}   0.054762    0.000051    0.041082    0.068839    0.054573    718.27    771.60    1.000
r(C<->G){all}   0.041638    0.000052    0.027495    0.055087    0.041212    865.25    907.53    1.000
r(C<->T){all}   0.620749    0.000478    0.576920    0.661524    0.620833    410.42    510.14    1.000
r(G<->T){all}   0.025060    0.000039    0.013636    0.037554    0.024813    586.14    669.90    1.001
pi(A){all}      0.328907    0.000154    0.306444    0.355033    0.328711    861.38    901.38    1.000
pi(C){all}      0.236693    0.000107    0.215692    0.256676    0.236531    756.15    827.90    1.000
pi(G){all}      0.214890    0.000118    0.194189    0.236089    0.214773    704.42    746.15    1.001
pi(T){all}      0.219510    0.000102    0.199966    0.239241    0.219327    617.88    661.69    1.000
alpha{1,2}      0.208312    0.000229    0.181524    0.238773    0.206892   1257.04   1335.81    1.000
alpha{3}        4.676802    0.762977    3.075306    6.410978    4.600007   1425.82   1463.41    1.000
pinvar{all}     0.125559    0.000726    0.073897    0.177822    0.124561   1282.91   1356.19    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	-6939.894242
Model 2: PositiveSelection	-6939.894242
Model 0: one-ratio	-6982.542395
Model 3: discrete	-6873.849457
Model 7: beta	-6877.893161
Model 8: beta&w>1	-6877.895608


Model 0 vs 1	85.29630600000019

Model 2 vs 1	0.0

Model 8 vs 7	0.004893999999694643