--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Nov 21 21:05:04 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-PF/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -26623.95        -26642.92
2     -26623.15        -26639.50
--------------------------------------
TOTAL   -26623.47        -26642.26
--------------------------------------


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

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.573215    0.001768    1.490235    1.654664    1.572249   1120.50   1292.65    1.000
r(A<->C){all}   0.082297    0.000035    0.070574    0.093553    0.082202   1046.24   1098.95    1.002
r(A<->G){all}   0.313229    0.000136    0.292007    0.336669    0.312727    720.83    754.45    1.002
r(A<->T){all}   0.113235    0.000078    0.096282    0.130320    0.112834    942.61    976.91    1.000
r(C<->G){all}   0.042193    0.000011    0.035855    0.048217    0.042125    890.70    966.51    1.000
r(C<->T){all}   0.386156    0.000147    0.362119    0.409767    0.386048    597.41    653.76    1.000
r(G<->T){all}   0.062890    0.000025    0.053295    0.072673    0.062734    952.47   1049.70    1.000
pi(A){all}      0.211257    0.000021    0.202273    0.220059    0.211330    699.29    755.83    1.000
pi(C){all}      0.290236    0.000025    0.280494    0.299757    0.290204    767.64    859.72    1.000
pi(G){all}      0.284784    0.000025    0.274627    0.294515    0.284894    713.26    766.30    1.000
pi(T){all}      0.213723    0.000019    0.205224    0.222305    0.213588    787.01    864.52    1.000
alpha{1,2}      0.091164    0.000010    0.085219    0.097377    0.091094   1079.61   1188.41    1.000
alpha{3}        7.769589    1.454497    5.461478   10.076630    7.663893   1268.47   1323.75    1.000
pinvar{all}     0.292227    0.000192    0.265819    0.320015    0.292154   1232.12   1366.56    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	-24565.669356
Model 0: one-ratio	-24706.841833
Model 3: discrete	-24514.70771
Model 7: beta	-24531.162641
Model 8: beta&w>1	-24523.020789


Model 0 vs 1	282.34505799999897

Model 2 vs 1	1.0399999882793054E-4

Model 8 vs 7	16.283704000001308

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-PF)

            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