--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Nov 16 02:42:26 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/241/endos-PB/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/241/endos-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/241/endos-PB/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/241/endos-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -1034.90         -1053.40
2      -1035.07         -1058.14
--------------------------------------
TOTAL    -1034.98         -1057.45
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/241/endos-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/241/endos-PB/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/241/endos-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.863136    0.021989    0.599122    1.171308    0.847059   1227.64   1273.68    1.000
r(A<->C){all}   0.058287    0.000649    0.015551    0.111912    0.054851    539.14    625.23    1.003
r(A<->G){all}   0.159413    0.002739    0.065851    0.261017    0.152574    548.35    590.34    1.000
r(A<->T){all}   0.148576    0.004208    0.029406    0.273836    0.141780    351.68    390.19    1.000
r(C<->G){all}   0.027806    0.000157    0.005802    0.052689    0.026196    885.66    886.53    1.000
r(C<->T){all}   0.563357    0.007302    0.400954    0.724100    0.563382    480.71    486.62    1.000
r(G<->T){all}   0.042561    0.000589    0.004372    0.091429    0.037802    771.67    941.43    1.002
pi(A){all}      0.264085    0.000514    0.221633    0.310340    0.263245    961.17   1032.97    1.000
pi(C){all}      0.320399    0.000584    0.272469    0.368952    0.320476   1075.12   1103.42    1.000
pi(G){all}      0.296258    0.000531    0.249833    0.340095    0.296015   1240.91   1302.34    1.000
pi(T){all}      0.119259    0.000288    0.088493    0.153409    0.118241    922.32    998.44    1.000
alpha{1,2}      0.107837    0.000753    0.061004    0.165277    0.105908   1156.75   1224.56    1.000
alpha{3}        2.155340    0.650239    0.820605    3.719296    2.017830   1007.36   1199.36    1.000
pinvar{all}     0.326241    0.007543    0.147511    0.490026    0.330972   1122.50   1175.32    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	-947.591513
Model 2: PositiveSelection	-947.591513
Model 0: one-ratio	-954.840262
Model 3: discrete	-944.979338
Model 7: beta	-945.027418
Model 8: beta&w>1	-945.02786


Model 0 vs 1	14.497498000000178

Model 2 vs 1	0.0

Model 8 vs 7	8.840000000418513E-4