--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu Nov 10 18:06:32 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-PD/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6052.18         -6068.56
2      -6051.92         -6068.98
--------------------------------------
TOTAL    -6052.04         -6068.79
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/191/CG8303-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/191/CG8303-PD/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-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.376891    0.007187    1.212918    1.539654    1.375829   1231.25   1283.81    1.001
r(A<->C){all}   0.095972    0.000175    0.071688    0.122512    0.095375   1147.73   1176.08    1.001
r(A<->G){all}   0.267687    0.000615    0.221187    0.317743    0.266431    807.16    838.83    1.000
r(A<->T){all}   0.065579    0.000194    0.039232    0.091536    0.064894    827.71    898.20    1.000
r(C<->G){all}   0.073981    0.000097    0.054615    0.092158    0.073664   1120.48   1193.96    1.000
r(C<->T){all}   0.443049    0.000757    0.387428    0.493139    0.442460    744.37    810.86    1.000
r(G<->T){all}   0.053733    0.000108    0.034534    0.075514    0.053310   1078.67   1196.18    1.000
pi(A){all}      0.213731    0.000095    0.193974    0.232410    0.213655    863.16    975.51    1.000
pi(C){all}      0.299860    0.000108    0.280379    0.321254    0.299759   1056.21   1064.10    1.000
pi(G){all}      0.263793    0.000106    0.244780    0.284461    0.263477   1049.53   1079.71    1.000
pi(T){all}      0.222616    0.000083    0.204745    0.240286    0.222585   1205.39   1239.35    1.000
alpha{1,2}      0.104280    0.000066    0.089210    0.120185    0.103947   1174.97   1337.98    1.000
alpha{3}        3.687562    0.720289    2.266047    5.393253    3.575785   1361.35   1431.18    1.000
pinvar{all}     0.384432    0.000809    0.328207    0.440031    0.385335   1410.93   1455.97    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	-5574.601456
Model 2: PositiveSelection	-5574.601479
Model 0: one-ratio	-5595.505515
Model 3: discrete	-5548.157414
Model 7: beta	-5548.298229
Model 8: beta&w>1	-5547.921762


Model 0 vs 1	41.80811799999901

Model 2 vs 1	4.599999920174014E-5

Model 8 vs 7	0.7529340000000957