--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Dec 10 18:28:29 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-PF/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -19574.27        -19591.15
2     -19574.24        -19591.97
--------------------------------------
TOTAL   -19574.25        -19591.64
--------------------------------------


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

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.207474    0.001629    1.130149    1.284942    1.207563   1282.00   1389.40    1.000
r(A<->C){all}   0.058845    0.000029    0.049164    0.069884    0.058675    930.83    971.52    1.001
r(A<->G){all}   0.284328    0.000164    0.259685    0.308688    0.284274    878.45    886.20    1.001
r(A<->T){all}   0.096858    0.000091    0.077889    0.115338    0.096620    662.30    754.85    1.000
r(C<->G){all}   0.026906    0.000009    0.021147    0.032790    0.026848    948.09   1059.66    1.000
r(C<->T){all}   0.484903    0.000233    0.456949    0.515437    0.484711    696.38    720.38    1.001
r(G<->T){all}   0.048160    0.000030    0.037384    0.058937    0.048042   1154.53   1168.39    1.000
pi(A){all}      0.266930    0.000030    0.256979    0.278684    0.266975   1008.68   1017.82    1.000
pi(C){all}      0.261743    0.000028    0.251442    0.272177    0.261865    957.70   1071.02    1.000
pi(G){all}      0.304539    0.000031    0.293654    0.315212    0.304363    977.51   1017.67    1.000
pi(T){all}      0.166788    0.000020    0.158158    0.175481    0.166801    859.79    985.86    1.000
alpha{1,2}      0.088573    0.000015    0.081574    0.096647    0.088572    910.27   1142.46    1.000
alpha{3}        8.235864    1.799719    5.780923   11.024210    8.132401   1501.00   1501.00    1.000
pinvar{all}     0.396692    0.000208    0.370470    0.426531    0.396466   1391.44   1433.30    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	-17979.696617
Model 2: PositiveSelection	-17979.696643
Model 0: one-ratio	-18002.62548
Model 3: discrete	-17960.642716
Model 7: beta	-17967.956561
Model 8: beta&w>1	-17966.815377


Model 0 vs 1	45.85772599999473

Model 2 vs 1	5.199999577598646E-5

Model 8 vs 7	2.282368000000133