--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Nov 12 06:00:54 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb_adops
tcoffee.bin=t_coffee_ADOPS
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/200/CG9485-PE/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/200/CG9485-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/200/CG9485-PE/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/200/CG9485-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -18442.35        -18458.82
2     -18442.08        -18461.12
--------------------------------------
TOTAL   -18442.20        -18460.52
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/200/CG9485-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/200/CG9485-PE/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/200/CG9485-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.443493    0.002399    1.347477    1.536372    1.443360   1355.73   1406.92    1.001
r(A<->C){all}   0.096105    0.000059    0.081506    0.111075    0.095845    779.75    806.47    1.000
r(A<->G){all}   0.278755    0.000185    0.253583    0.305420    0.278557    820.63    854.57    1.000
r(A<->T){all}   0.119692    0.000112    0.099913    0.141759    0.119314    885.79    960.53    1.000
r(C<->G){all}   0.044835    0.000019    0.037216    0.054293    0.044761    865.02    885.52    1.001
r(C<->T){all}   0.383447    0.000218    0.356730    0.413327    0.383443    779.95    786.80    1.000
r(G<->T){all}   0.077166    0.000047    0.064335    0.090396    0.077073    964.18   1107.37    1.000
pi(A){all}      0.217635    0.000035    0.206537    0.229389    0.217504    877.20    970.07    1.000
pi(C){all}      0.290079    0.000037    0.279033    0.302627    0.289904    808.61    922.94    1.000
pi(G){all}      0.277126    0.000037    0.264609    0.288545    0.277074   1175.07   1207.30    1.001
pi(T){all}      0.215159    0.000029    0.204851    0.225547    0.215108    881.22    953.46    1.003
alpha{1,2}      0.129043    0.000033    0.117349    0.140089    0.128760   1436.82   1452.52    1.000
alpha{3}        6.304459    1.210395    4.360364    8.443409    6.191276   1491.93   1496.46    1.000
pinvar{all}     0.313402    0.000318    0.278929    0.348552    0.313513   1135.10   1191.35    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 1: NearlyNeutral	-17318.601925
Model 2: PositiveSelection	-17318.602128
Model 0: one-ratio	-17455.212255
Model 3: discrete	-17250.559313
Model 7: beta	-17252.27484
Model 8: beta&w>1	-17251.474405


Model 0 vs 1	273.22065999999904

Model 2 vs 1	4.059999992023222E-4

Model 8 vs 7	1.6008699999947567