--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Oct 31 18:42:30 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_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/data/res/NS3_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/res/NS3_3/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_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -15815.71        -15853.66
2     -15814.62        -15855.37
--------------------------------------
TOTAL   -15815.03        -15854.84
--------------------------------------


Model parameter summaries over the runs sampled in files
"/data/res/NS3_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/res/NS3_3/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_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         8.425141    0.164025    7.646933    9.207501    8.407531    744.39    766.30    1.000
r(A<->C){all}   0.035718    0.000015    0.028219    0.042966    0.035718    775.16    884.98    1.002
r(A<->G){all}   0.208060    0.000141    0.184214    0.229804    0.207683    459.68    463.36    1.000
r(A<->T){all}   0.046224    0.000020    0.037373    0.054740    0.046128    861.91    913.43    1.000
r(C<->G){all}   0.016924    0.000014    0.009826    0.024158    0.016635    712.55    809.21    1.000
r(C<->T){all}   0.669157    0.000206    0.641284    0.697423    0.669348    436.61    437.49    1.001
r(G<->T){all}   0.023917    0.000020    0.015102    0.031945    0.023817    837.42    933.67    1.000
pi(A){all}      0.359492    0.000061    0.343688    0.373944    0.359424    740.06    758.48    1.004
pi(C){all}      0.215378    0.000041    0.202210    0.227201    0.215382    588.08    703.51    1.002
pi(G){all}      0.227439    0.000049    0.214465    0.241555    0.227227    597.84    675.02    1.000
pi(T){all}      0.197692    0.000037    0.186675    0.210501    0.197489    625.72    675.81    1.000
alpha{1,2}      0.158258    0.000043    0.146023    0.171408    0.157968   1366.34   1404.87    1.001
alpha{3}        5.668751    0.757254    4.170135    7.526887    5.599271   1501.00   1501.00    1.000
pinvar{all}     0.109799    0.000284    0.078068    0.142634    0.109073    985.58   1164.35    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	-15117.740977
Model 2: PositiveSelection	-15117.740977
Model 0: one-ratio	-15166.398429
Model 3: discrete	-14954.584833
Model 7: beta	-14953.852837
Model 8: beta&w>1	-14953.797678


Model 0 vs 1	97.31490400000257

Model 2 vs 1	0.0

Model 8 vs 7	0.11031799999909708