--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sun Oct 28 02:28:18 GMT 2018
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=/data/res/NS3_1/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/data/res/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/res/NS3_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 /data/res/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -15329.36        -15373.58
2     -15329.73        -15376.38
--------------------------------------
TOTAL   -15329.53        -15375.74
--------------------------------------


Model parameter summaries over the runs sampled in files
"/data/res/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/res/NS3_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 "/data/res/NS3_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}         8.410911    0.186214    7.601417    9.274114    8.392660    435.22    483.62    1.000
r(A<->C){all}   0.036342    0.000016    0.028374    0.043874    0.036246    579.71    712.87    1.000
r(A<->G){all}   0.198526    0.000124    0.177482    0.220228    0.198371    349.50    384.85    1.001
r(A<->T){all}   0.039138    0.000018    0.031361    0.047800    0.038980    577.10    669.73    1.000
r(C<->G){all}   0.017187    0.000012    0.010556    0.024205    0.017076    696.07    749.56    1.004
r(C<->T){all}   0.688017    0.000190    0.662993    0.717290    0.688240    274.10    328.56    1.003
r(G<->T){all}   0.020790    0.000016    0.013057    0.028635    0.020591    682.09    744.04    1.000
pi(A){all}      0.360404    0.000060    0.344110    0.374796    0.360246    811.17    820.48    1.001
pi(C){all}      0.215973    0.000041    0.203936    0.228390    0.215955    692.99    717.90    1.000
pi(G){all}      0.229875    0.000046    0.216893    0.243446    0.229823    493.80    672.33    1.000
pi(T){all}      0.193748    0.000034    0.182645    0.204920    0.193843    801.53    802.63    1.001
alpha{1,2}      0.164246    0.000047    0.151390    0.178539    0.163955   1176.86   1242.32    1.000
alpha{3}        6.235556    0.965629    4.525527    8.321555    6.156852   1407.84   1418.31    1.000
pinvar{all}     0.130268    0.000320    0.097066    0.166054    0.129908   1025.20   1086.61    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	-14756.824397
Model 2: PositiveSelection	-14756.824397
Model 0: one-ratio	-14782.633196
Model 3: discrete	-14582.276698
Model 7: beta	-14583.680656
Model 8: beta&w>1	-14583.685229


Model 0 vs 1	51.617598000000726

Model 2 vs 1	0.0

Model 8 vs 7	0.009146000000328058