--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 18 20:29:02 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/274/Hsc70-3-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-3-PC/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/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -5363.20         -5379.40
2      -5363.08         -5383.35
--------------------------------------
TOTAL    -5363.14         -5382.68
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-3-PC/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/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.676422    0.002202    0.587626    0.768165    0.674507   1354.94   1371.63    1.000
r(A<->C){all}   0.051050    0.000129    0.030719    0.073907    0.050361    834.53    964.47    1.000
r(A<->G){all}   0.175997    0.000597    0.130049    0.225277    0.175568    756.28    919.88    1.000
r(A<->T){all}   0.054288    0.000278    0.021413    0.085922    0.052965    897.15   1019.01    1.001
r(C<->G){all}   0.056226    0.000077    0.039697    0.073440    0.055778   1081.91   1195.00    1.000
r(C<->T){all}   0.604434    0.000981    0.540164    0.661228    0.604250    776.05    874.70    1.000
r(G<->T){all}   0.058004    0.000130    0.035226    0.079707    0.057265   1188.55   1207.46    1.000
pi(A){all}      0.226782    0.000090    0.209088    0.246017    0.226620    835.02    941.83    1.000
pi(C){all}      0.292682    0.000091    0.274187    0.310665    0.292539   1229.50   1248.25    1.001
pi(G){all}      0.292272    0.000099    0.272858    0.311793    0.292265    920.62   1030.85    1.000
pi(T){all}      0.188264    0.000069    0.171652    0.203455    0.188174    888.46    940.97    1.000
alpha{1,2}      0.033267    0.000411    0.000184    0.067247    0.031786    855.54    874.36    1.000
alpha{3}        4.123766    0.991690    2.425675    6.119612    4.017863   1337.91   1363.59    1.000
pinvar{all}     0.511172    0.000695    0.459691    0.563002    0.511903   1247.68   1374.34    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	-4932.66204
Model 2: PositiveSelection	-4932.859411
Model 0: one-ratio	-4932.85941
Model 3: discrete	-4932.136197
Model 7: beta	-4932.138108
Model 8: beta&w>1	-4932.140858


Model 0 vs 1	0.39473999999972875

Model 2 vs 1	0.3947420000004058

Model 8 vs 7	0.005499999999301508