--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu May 03 17:49:50 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_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DNGB3/NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_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 /opt/ADOPS/DNGB3/NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -19412.71        -19456.20
2     -19412.33        -19455.77
--------------------------------------
TOTAL   -19412.50        -19456.01
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DNGB3/NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_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 "/opt/ADOPS/DNGB3/NS5_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}         5.297031    0.064043    4.825848    5.795090    5.282866    493.56    592.04    1.001
r(A<->C){all}   0.046392    0.000019    0.037077    0.054498    0.046230    492.32    656.84    1.001
r(A<->G){all}   0.168282    0.000091    0.149628    0.187338    0.168227    538.91    543.15    1.000
r(A<->T){all}   0.057248    0.000027    0.047805    0.068117    0.057126    577.24    585.06    1.000
r(C<->G){all}   0.032049    0.000019    0.024124    0.040523    0.031906    442.26    575.36    1.000
r(C<->T){all}   0.665076    0.000196    0.638890    0.692134    0.665039    311.35    398.79    1.000
r(G<->T){all}   0.030953    0.000024    0.021691    0.040940    0.030732    706.13    808.78    1.000
pi(A){all}      0.351923    0.000048    0.338122    0.365305    0.352199    685.48    738.24    1.000
pi(C){all}      0.220942    0.000033    0.209613    0.232030    0.220824    780.26    785.25    1.000
pi(G){all}      0.246805    0.000042    0.234659    0.260561    0.246739    593.58    639.11    1.000
pi(T){all}      0.180329    0.000026    0.170598    0.190454    0.180238    600.79    715.31    1.000
alpha{1,2}      0.205354    0.000088    0.187054    0.223256    0.204923   1193.03   1243.98    1.000
alpha{3}        4.432837    0.540636    3.055684    5.848915    4.351101   1373.61   1428.62    1.000
pinvar{all}     0.096954    0.000285    0.064990    0.130298    0.096312   1105.59   1134.83    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, 	-16995.687176