--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Dec 20 05:36:06 WET 2017
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/DGA_B3/NS5_5/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_5/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/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -23288.12        -23323.87
2     -23288.87        -23329.17
--------------------------------------
TOTAL   -23288.42        -23328.48
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_5/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/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         8.061799    0.129426    7.374975    8.768002    8.044148    406.71    489.73    1.000
r(A<->C){all}   0.035072    0.000010    0.028731    0.041246    0.035008    378.86    605.98    1.000
r(A<->G){all}   0.194707    0.000095    0.175852    0.213502    0.194346    364.83    369.54    1.000
r(A<->T){all}   0.043532    0.000015    0.035703    0.050999    0.043615    832.63    858.04    1.000
r(C<->G){all}   0.022492    0.000011    0.016124    0.028837    0.022345    807.43    841.25    1.002
r(C<->T){all}   0.680304    0.000147    0.657529    0.704235    0.680692    277.45    310.09    1.000
r(G<->T){all}   0.023893    0.000016    0.016436    0.031805    0.023793    569.19    675.45    1.001
pi(A){all}      0.365063    0.000042    0.351920    0.376659    0.365069    532.43    650.61    1.000
pi(C){all}      0.224436    0.000028    0.214117    0.234494    0.224285    590.99    613.37    1.000
pi(G){all}      0.231947    0.000033    0.220742    0.242907    0.232079    578.71    691.51    1.000
pi(T){all}      0.178554    0.000024    0.169176    0.188422    0.178432    396.28    464.12    1.000
alpha{1,2}      0.189319    0.000053    0.175460    0.203537    0.189102   1264.18   1306.72    1.000
alpha{3}        6.620637    0.912778    4.852459    8.529687    6.546054   1382.33   1441.67    1.000
pinvar{all}     0.138172    0.000205    0.109989    0.166131    0.138298    938.31   1027.36    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, 	-22524.808358