--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu May 03 20:49:10 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_4/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DNGB3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_4/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_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -20637.19        -20676.67
2     -20637.07        -20682.03
--------------------------------------
TOTAL   -20637.13        -20681.34
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DNGB3/NS5_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_4/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_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         7.193089    0.119327    6.505175    7.860635    7.177949    436.64    508.89    1.000
r(A<->C){all}   0.040402    0.000015    0.032937    0.047841    0.040328    758.90    795.49    1.002
r(A<->G){all}   0.189128    0.000095    0.170652    0.208067    0.188689    464.06    503.44    1.000
r(A<->T){all}   0.051212    0.000022    0.042340    0.060503    0.051069    815.28    884.35    1.001
r(C<->G){all}   0.025066    0.000015    0.017559    0.032405    0.024863    692.94    815.36    1.000
r(C<->T){all}   0.672263    0.000166    0.647259    0.697231    0.672732    465.56    480.77    1.000
r(G<->T){all}   0.021929    0.000019    0.013969    0.030458    0.021699    718.68    751.23    1.002
pi(A){all}      0.357485    0.000045    0.345480    0.371937    0.357175    530.52    701.81    1.001
pi(C){all}      0.222591    0.000030    0.211992    0.233529    0.222635    464.26    675.13    1.000
pi(G){all}      0.239334    0.000036    0.227867    0.251073    0.239339    463.84    643.56    1.001
pi(T){all}      0.180591    0.000025    0.170889    0.190177    0.180515    725.86    734.08    1.000
alpha{1,2}      0.183895    0.000053    0.170881    0.198623    0.183654   1174.16   1236.07    1.003
alpha{3}        6.343530    0.996283    4.486619    8.240392    6.227889   1162.82   1331.91    1.000
pinvar{all}     0.135224    0.000211    0.106306    0.162218    0.135341    921.48   1042.94    1.001
------------------------------------------------------------------------------------------------------
* 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, 	-19787.963419