--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 25 22:04:22 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/1/5PtaseI-PF/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/5PtaseI-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/5PtaseI-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/1/5PtaseI-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -8847.52         -8865.80
2      -8847.63         -8862.42
--------------------------------------
TOTAL    -8847.57         -8865.14
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/5PtaseI-PF/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/5PtaseI-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/1/5PtaseI-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}         0.887435    0.002468    0.793564    0.988190    0.886320   1399.09   1450.04    1.000
r(A<->C){all}   0.096964    0.000108    0.076210    0.115626    0.096577   1020.64   1117.10    1.000
r(A<->G){all}   0.257464    0.000376    0.216434    0.294368    0.257452    750.30    890.44    1.000
r(A<->T){all}   0.101488    0.000135    0.080163    0.125651    0.101215   1097.89   1117.57    1.000
r(C<->G){all}   0.091401    0.000109    0.070795    0.111304    0.091060    841.44   1018.91    1.001
r(C<->T){all}   0.385959    0.000487    0.341569    0.427906    0.385526    807.66    876.09    1.000
r(G<->T){all}   0.066724    0.000101    0.048357    0.086950    0.066391    988.92   1124.70    1.000
pi(A){all}      0.280879    0.000072    0.264816    0.297789    0.280890   1125.97   1143.40    1.000
pi(C){all}      0.257914    0.000070    0.241128    0.273970    0.257947   1152.15   1161.35    1.000
pi(G){all}      0.235088    0.000064    0.219931    0.250891    0.234953    754.16   1028.41    1.000
pi(T){all}      0.226119    0.000064    0.210238    0.241625    0.226067    933.41   1063.33    1.000
alpha{1,2}      0.230197    0.000527    0.185426    0.273018    0.228179   1132.01   1275.39    1.000
alpha{3}        3.178917    0.635412    1.795807    4.728869    3.067282    972.67   1148.74    1.000
pinvar{all}     0.374775    0.001089    0.310911    0.440002    0.376342   1137.29   1167.15    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	-8203.203783
Model 2: PositiveSelection	-8203.203783
Model 0: one-ratio	-8285.96666
Model 3: discrete	-8186.471264
Model 7: beta	-8186.591177
Model 8: beta&w>1	-8186.591304


Model 0 vs 1	165.52575399999841

Model 2 vs 1	0.0

Model 8 vs 7	2.539999986765906E-4