--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 25 16:37:32 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/1/26-29-p-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/26-29-p-PA/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/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6459.17         -6478.37
2      -6458.33         -6475.80
--------------------------------------
TOTAL    -6458.66         -6477.75
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/26-29-p-PA/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/1/26-29-p-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.395727    0.006669    1.245451    1.567078    1.392888   1417.92   1459.46    1.000
r(A<->C){all}   0.079864    0.000133    0.057824    0.102788    0.079302   1082.21   1163.84    1.000
r(A<->G){all}   0.237901    0.000491    0.194278    0.280108    0.237253    943.56    959.58    1.000
r(A<->T){all}   0.139145    0.000394    0.099716    0.175798    0.138606    861.41    906.85    1.000
r(C<->G){all}   0.056093    0.000065    0.041772    0.072933    0.055398   1165.38   1217.40    1.000
r(C<->T){all}   0.417615    0.000697    0.366654    0.470134    0.417678    843.37    861.39    1.000
r(G<->T){all}   0.069381    0.000143    0.047029    0.093248    0.068709   1031.95   1042.74    1.000
pi(A){all}      0.231037    0.000097    0.212153    0.249852    0.231068   1122.19   1160.88    1.000
pi(C){all}      0.294517    0.000097    0.276345    0.315336    0.294294    981.31   1117.82    1.000
pi(G){all}      0.264342    0.000098    0.246259    0.284971    0.264201   1146.48   1181.75    1.001
pi(T){all}      0.210103    0.000078    0.193861    0.228494    0.209995   1124.06   1132.98    1.001
alpha{1,2}      0.124657    0.000085    0.106656    0.142731    0.124103   1165.41   1314.09    1.000
alpha{3}        4.077650    0.827212    2.471403    5.978732    3.976993    759.08   1063.61    1.000
pinvar{all}     0.298656    0.000966    0.236553    0.357737    0.299561   1095.58   1265.72    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	-6059.250602
Model 2: PositiveSelection	-6059.250602
Model 0: one-ratio	-6101.198072
Model 3: discrete	-6025.977293
Model 7: beta	-6026.099343
Model 8: beta&w>1	-6026.10085


Model 0 vs 1	83.89494000000013

Model 2 vs 1	0.0

Model 8 vs 7	0.003013999999893713