--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Nov 19 00:07:46 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/267/heph-PQ/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/267/heph-PQ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/267/heph-PQ/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/267/heph-PQ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -4602.31         -4625.05
2      -4601.39         -4618.12
--------------------------------------
TOTAL    -4601.75         -4624.36
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/267/heph-PQ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/267/heph-PQ/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/267/heph-PQ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.836180    0.004484    0.713225    0.972442    0.832610    983.90   1242.45    1.000
r(A<->C){all}   0.089550    0.000208    0.061020    0.117268    0.088849   1058.34   1123.77    1.000
r(A<->G){all}   0.253958    0.000876    0.193207    0.308745    0.253526    860.46    918.56    1.000
r(A<->T){all}   0.083936    0.000446    0.045029    0.127624    0.082380    866.97    944.17    1.000
r(C<->G){all}   0.052964    0.000094    0.034989    0.072490    0.052519    924.22   1020.70    1.001
r(C<->T){all}   0.442562    0.001249    0.375322    0.513019    0.441897    893.91    918.92    1.001
r(G<->T){all}   0.077030    0.000243    0.047449    0.107919    0.076501   1123.96   1236.53    1.001
pi(A){all}      0.235354    0.000118    0.216044    0.258509    0.235282   1024.87   1082.40    1.000
pi(C){all}      0.329975    0.000135    0.306793    0.351716    0.329827   1079.98   1220.89    1.000
pi(G){all}      0.248699    0.000120    0.228251    0.270516    0.248768   1157.11   1194.00    1.001
pi(T){all}      0.185971    0.000090    0.166892    0.203250    0.185805   1104.39   1171.17    1.001
alpha{1,2}      0.150788    0.000229    0.122431    0.180736    0.149648   1301.95   1401.48    1.000
alpha{3}        4.087019    1.051216    2.158417    6.031862    3.945916   1216.70   1350.23    1.000
pinvar{all}     0.495563    0.000889    0.438677    0.555465    0.496249    918.35   1143.65    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	-4227.346774
Model 2: PositiveSelection	-4227.346774
Model 0: one-ratio	-4232.966012
Model 3: discrete	-4219.192004
Model 7: beta	-4219.296233
Model 8: beta&w>1	-4219.297269


Model 0 vs 1	11.238476000000446

Model 2 vs 1	0.0

Model 8 vs 7	0.0020719999993161764