--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Nov 21 14:03:34 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/3/ACC-PB/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -26622.08        -26643.25
2     -26623.77        -26641.26
--------------------------------------
TOTAL   -26622.61        -26642.68
--------------------------------------


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

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.572864    0.001844    1.487657    1.654629    1.571973   1320.81   1410.90    1.000
r(A<->C){all}   0.082497    0.000034    0.070955    0.093833    0.082220    910.52   1002.91    1.000
r(A<->G){all}   0.314054    0.000131    0.293011    0.336018    0.313619    866.74    894.03    1.000
r(A<->T){all}   0.113188    0.000077    0.094955    0.129599    0.113062    983.01   1050.30    1.000
r(C<->G){all}   0.042194    0.000011    0.035776    0.048369    0.042126   1113.83   1118.42    1.000
r(C<->T){all}   0.385143    0.000142    0.360243    0.406597    0.385129    801.07    873.93    1.000
r(G<->T){all}   0.062924    0.000025    0.053481    0.072691    0.062688   1064.02   1098.75    1.001
pi(A){all}      0.210983    0.000020    0.201901    0.219119    0.211025    927.85    939.39    1.000
pi(C){all}      0.290154    0.000023    0.280085    0.299172    0.290047    918.93   1002.66    1.000
pi(G){all}      0.284796    0.000024    0.275630    0.294350    0.284856    882.53    912.29    1.000
pi(T){all}      0.214067    0.000019    0.204823    0.221968    0.214157    737.54    779.36    1.000
alpha{1,2}      0.091150    0.000009    0.085180    0.097121    0.091079   1231.52   1253.72    1.000
alpha{3}        7.805217    1.491383    5.679169   10.356290    7.679660   1336.24   1418.62    1.000
pinvar{all}     0.292626    0.000197    0.266299    0.321154    0.292798   1303.99   1368.61    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	-24565.669304
Model 2: PositiveSelection	-24565.66932
Model 0: one-ratio	-24706.841833
Model 3: discrete	-24513.827021
Model 7: beta	-24531.162579
Model 8: beta&w>1	-24523.020721


Model 0 vs 1	282.34505799999897

Model 2 vs 1	3.2000003557186574E-5

Model 8 vs 7	16.283715999998094

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118)
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: D_melanogaster_ACC-PB)

            Pr(w>1)     post mean +- SE for w

   280 N      0.655         1.196 +- 0.433
   752 S      0.734         1.265 +- 0.410
   757 Y      0.563         1.079 +- 0.499
   815 L      0.692         1.220 +- 0.437
  2136 A      0.515         1.026 +- 0.510