--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu May 03 15:25:14 WEST 2018
codeml.models=
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/DNGB3/NS5_2/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DNGB3/NS5_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_2/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/DNGB3/NS5_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -19801.38        -19845.69
2     -19804.46        -19841.69
--------------------------------------
TOTAL   -19802.03        -19845.01
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DNGB3/NS5_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_2/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/DNGB3/NS5_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         6.741353    0.125622    6.069496    7.436466    6.730656    347.02    474.98    1.000
r(A<->C){all}   0.039397    0.000016    0.031533    0.047190    0.039306    634.32    738.58    1.000
r(A<->G){all}   0.191637    0.000102    0.172954    0.212045    0.191567    330.06    403.59    1.000
r(A<->T){all}   0.044801    0.000020    0.036169    0.053235    0.044764    721.85    766.91    1.000
r(C<->G){all}   0.023174    0.000016    0.015138    0.030834    0.023034    592.26    778.22    1.000
r(C<->T){all}   0.675562    0.000169    0.651342    0.701883    0.675790    301.76    385.50    1.000
r(G<->T){all}   0.025428    0.000022    0.016478    0.034468    0.025081    825.61    844.92    1.000
pi(A){all}      0.359238    0.000045    0.346001    0.372206    0.359189    683.55    697.10    1.000
pi(C){all}      0.223553    0.000030    0.211911    0.233479    0.223635    704.85    728.21    1.000
pi(G){all}      0.235098    0.000036    0.223904    0.246740    0.234950    643.13    764.05    1.001
pi(T){all}      0.182111    0.000024    0.172266    0.191351    0.181990    575.16    692.82    1.000
alpha{1,2}      0.187620    0.000067    0.171547    0.203710    0.187444   1158.92   1196.29    1.000
alpha{3}        4.934990    0.630612    3.514407    6.530729    4.854052   1407.91   1454.45    1.000
pinvar{all}     0.145228    0.000257    0.113774    0.176995    0.144878   1055.51   1070.47    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: One dN/dS ratio for branches, 	-18257.137563