--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Dec 10 19:42:32 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/443/zip-PG/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/443/zip-PG/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/443/zip-PG/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/443/zip-PG/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -19514.71        -19532.34
2     -19514.59        -19532.20
--------------------------------------
TOTAL   -19514.65        -19532.27
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/443/zip-PG/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/443/zip-PG/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/443/zip-PG/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.212547    0.001673    1.134064    1.291164    1.211241   1277.60   1371.89    1.000
r(A<->C){all}   0.058756    0.000031    0.047474    0.069794    0.058578   1057.42   1081.69    1.000
r(A<->G){all}   0.284397    0.000172    0.260493    0.311481    0.283925    751.46    841.28    1.001
r(A<->T){all}   0.097241    0.000094    0.078609    0.115690    0.096926    725.98    800.58    1.000
r(C<->G){all}   0.026858    0.000009    0.021175    0.032728    0.026812   1093.48   1171.49    1.000
r(C<->T){all}   0.484521    0.000249    0.454882    0.515912    0.484214    689.41    789.48    1.002
r(G<->T){all}   0.048228    0.000030    0.037548    0.059087    0.048026    932.02   1038.99    1.000
pi(A){all}      0.266612    0.000030    0.255852    0.277317    0.266600    824.17    874.23    1.001
pi(C){all}      0.261962    0.000029    0.250972    0.272751    0.261929   1010.67   1033.38    1.000
pi(G){all}      0.305020    0.000032    0.293466    0.315873    0.304741    843.13    939.92    1.000
pi(T){all}      0.166406    0.000018    0.158017    0.174782    0.166367    946.81    975.83    1.002
alpha{1,2}      0.088166    0.000015    0.080907    0.096235    0.088055   1277.70   1295.11    1.000
alpha{3}        8.226915    1.918591    5.694567   11.019890    8.088883   1501.00   1501.00    1.000
pinvar{all}     0.395405    0.000220    0.366937    0.424498    0.395259   1313.02   1407.01    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	-17922.60291
Model 2: PositiveSelection	-17922.60291
Model 0: one-ratio	-17945.954531
Model 3: discrete	-17903.295745
Model 7: beta	-17911.101232
Model 8: beta&w>1	-17909.940876


Model 0 vs 1	46.70324199999595

Model 2 vs 1	0.0

Model 8 vs 7	2.32071200000064