--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Nov 14 16:19:45 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/220/Cyp6v1-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/220/Cyp6v1-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/220/Cyp6v1-PA/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/220/Cyp6v1-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -5158.56         -5177.50
2      -5158.31         -5173.89
--------------------------------------
TOTAL    -5158.43         -5176.83
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/220/Cyp6v1-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/220/Cyp6v1-PA/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/220/Cyp6v1-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.986305    0.004859    0.855936    1.121954    0.986365   1145.67   1219.65    1.000
r(A<->C){all}   0.110595    0.000255    0.079235    0.141046    0.109652    978.87   1151.91    1.000
r(A<->G){all}   0.269722    0.000731    0.215601    0.320790    0.268841    702.67    810.63    1.000
r(A<->T){all}   0.066807    0.000273    0.035476    0.099520    0.065717   1099.62   1144.35    1.000
r(C<->G){all}   0.096393    0.000146    0.073579    0.120552    0.095966   1112.50   1113.28    1.000
r(C<->T){all}   0.427053    0.000913    0.370671    0.486095    0.427205    713.66    749.48    1.000
r(G<->T){all}   0.029430    0.000085    0.012657    0.047905    0.028744   1079.61   1289.04    1.000
pi(A){all}      0.186680    0.000091    0.167909    0.205286    0.186508    973.57   1058.93    1.002
pi(C){all}      0.322024    0.000117    0.300319    0.343222    0.322008    889.14   1020.82    1.000
pi(G){all}      0.285821    0.000114    0.265509    0.307088    0.285804   1024.75   1063.85    1.000
pi(T){all}      0.205476    0.000089    0.187442    0.224008    0.205354    922.55    967.66    1.000
alpha{1,2}      0.132250    0.000133    0.110177    0.153909    0.131666   1307.39   1404.19    1.000
alpha{3}        4.421903    1.174411    2.500993    6.581409    4.293353   1148.38   1256.77    1.000
pinvar{all}     0.408732    0.001059    0.342736    0.470742    0.409556   1284.39   1298.29    1.001
------------------------------------------------------------------------------------------------------
* 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	-4687.937156
Model 2: PositiveSelection	-4687.937156
Model 0: one-ratio	-4694.192222
Model 3: discrete	-4680.124975
Model 7: beta	-4680.140554
Model 8: beta&w>1	-4680.142584


Model 0 vs 1	12.51013199999943

Model 2 vs 1	0.0

Model 8 vs 7	0.004060000001118169