--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Tue Dec 19 19:12:18 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_1/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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 /opt/ADOPS/DGA_B3/NS5_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -19864.06        -19906.75
2     -19869.69        -19911.03
--------------------------------------
TOTAL   -19864.75        -19910.35
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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 "/opt/ADOPS/DGA_B3/NS5_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}         6.361077    0.106677    5.703953    6.951266    6.351700    296.49    372.16    1.000
r(A<->C){all}   0.042594    0.000017    0.034776    0.050435    0.042568    716.16    761.38    1.000
r(A<->G){all}   0.173508    0.000091    0.155239    0.191796    0.173197    602.32    602.59    1.000
r(A<->T){all}   0.046588    0.000023    0.036939    0.055144    0.046550    626.63    684.25    1.001
r(C<->G){all}   0.022141    0.000014    0.015154    0.029732    0.021956    701.67    798.03    1.001
r(C<->T){all}   0.685167    0.000168    0.660411    0.710964    0.685467    500.95    540.53    1.000
r(G<->T){all}   0.030001    0.000021    0.021118    0.038880    0.029740    610.93    732.42    1.000
pi(A){all}      0.352567    0.000046    0.339994    0.366552    0.352420    745.99    814.22    1.000
pi(C){all}      0.223430    0.000033    0.212836    0.234730    0.223298    601.96    621.84    1.000
pi(G){all}      0.241908    0.000038    0.229871    0.253928    0.241850    647.01    655.94    1.002
pi(T){all}      0.182095    0.000026    0.172905    0.192450    0.181977    720.17    819.74    1.001
alpha{1,2}      0.187107    0.000060    0.173159    0.203072    0.186852   1115.20   1228.09    1.000
alpha{3}        4.332707    0.456452    3.075915    5.614713    4.273949   1236.62   1368.81    1.000
pinvar{all}     0.119087    0.000268    0.086682    0.151238    0.119062   1099.61   1194.76    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, 	-18816.636425