--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu Nov 10 17:38:15 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/191/CG8303-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/191/CG8303-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/191/CG8303-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/191/CG8303-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6051.37         -6067.03
2      -6052.15         -6071.57
--------------------------------------
TOTAL    -6051.68         -6070.89
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/191/CG8303-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/191/CG8303-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/191/CG8303-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}         1.377318    0.007257    1.211682    1.538435    1.375000   1501.00   1501.00    1.000
r(A<->C){all}   0.096186    0.000177    0.069986    0.121094    0.095560    916.14    998.52    1.001
r(A<->G){all}   0.268585    0.000635    0.222641    0.318597    0.267342    796.95    935.35    1.000
r(A<->T){all}   0.065405    0.000198    0.039226    0.093392    0.064790    750.11    873.42    1.002
r(C<->G){all}   0.073720    0.000092    0.055910    0.093613    0.073416   1200.36   1233.40    1.003
r(C<->T){all}   0.442755    0.000824    0.385902    0.495250    0.443153    462.72    651.83    1.001
r(G<->T){all}   0.053348    0.000102    0.034282    0.072660    0.052833    758.37    850.68    1.000
pi(A){all}      0.213888    0.000094    0.194326    0.232475    0.213551    862.33    889.33    1.003
pi(C){all}      0.299613    0.000107    0.280426    0.319734    0.299797    928.06   1002.46    1.000
pi(G){all}      0.263689    0.000100    0.244450    0.282509    0.263630   1171.01   1182.22    1.000
pi(T){all}      0.222810    0.000083    0.206366    0.241991    0.222532    870.40    989.02    1.000
alpha{1,2}      0.104517    0.000066    0.087730    0.119797    0.104289   1277.20   1324.19    1.000
alpha{3}        3.698133    0.738771    2.080374    5.360746    3.588494   1232.49   1318.57    1.001
pinvar{all}     0.386240    0.000811    0.336313    0.446649    0.386339   1499.80   1500.40    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	-5567.541976
Model 2: PositiveSelection	-5567.542014
Model 0: one-ratio	-5589.146598
Model 3: discrete	-5541.681666
Model 7: beta	-5541.810101
Model 8: beta&w>1	-5541.433469


Model 0 vs 1	43.20924399999967

Model 2 vs 1	7.599999844387639E-5

Model 8 vs 7	0.7532640000008541