--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Dec 02 23:16:00 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/96/CG18304-PD/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/96/CG18304-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/96/CG18304-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/96/CG18304-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -24487.15        -24505.50
2     -24487.54        -24508.37
--------------------------------------
TOTAL   -24487.33        -24507.73
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/96/CG18304-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/96/CG18304-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/96/CG18304-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}         1.394498    0.001818    1.310928    1.479166    1.393626   1391.08   1440.03    1.000
r(A<->C){all}   0.089402    0.000036    0.078170    0.100948    0.089371    968.13   1028.66    1.000
r(A<->G){all}   0.250947    0.000119    0.229613    0.271781    0.250995    705.17    744.98    1.000
r(A<->T){all}   0.143224    0.000096    0.123744    0.161431    0.142938    790.04    874.08    1.000
r(C<->G){all}   0.053559    0.000016    0.045374    0.061100    0.053378    795.14    866.54    1.000
r(C<->T){all}   0.385537    0.000175    0.361055    0.411588    0.385282    721.73    754.63    1.000
r(G<->T){all}   0.077331    0.000040    0.064465    0.089422    0.077146    906.20    912.20    1.000
pi(A){all}      0.269168    0.000029    0.258883    0.279813    0.269253    700.19    798.83    1.000
pi(C){all}      0.273689    0.000030    0.263066    0.284004    0.273805    902.62    937.45    1.000
pi(G){all}      0.295366    0.000029    0.285035    0.306062    0.295316    781.29    850.44    1.000
pi(T){all}      0.161778    0.000018    0.154211    0.170806    0.161751    858.28    890.88    1.000
alpha{1,2}      0.168665    0.000053    0.154999    0.183025    0.168301   1166.15   1249.41    1.000
alpha{3}        4.930558    0.664500    3.482044    6.602602    4.841415   1375.96   1389.28    1.000
pinvar{all}     0.291020    0.000286    0.257701    0.322139    0.290967   1327.07   1372.10    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	-22541.637157
Model 2: PositiveSelection	-22541.637158
Model 0: one-ratio	-22861.417554
Model 3: discrete	-22457.22328
Model 7: beta	-22462.546464
Model 8: beta&w>1	-22456.789765


Model 0 vs 1	639.5607939999973

Model 2 vs 1	2.0000006770715117E-6

Model 8 vs 7	11.513397999995505

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: D_melanogaster_CG18304-PD)

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

   302 A      0.954*        1.182
   303 S      0.884         1.123
   316 I      0.871         1.112
   318 T      0.907         1.143
   319 A      0.766         1.023
   321 A      0.511         0.804
   324 S      0.798         1.049
   637 T      0.626         0.903
   638 V      0.956*        1.184
   653 N      0.851         1.095
   984 S      0.601         0.882

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_CG18304-PD)

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

    78 A      0.650         1.151 +- 0.493
   118 T      0.514         1.041 +- 0.490
   157 I      0.729         1.235 +- 0.449
   222 P      0.573         1.068 +- 0.521
   223 T      0.525         1.013 +- 0.534
   242 L      0.679         1.196 +- 0.456
   277 A      0.502         1.030 +- 0.490
   300 S      0.728         1.246 +- 0.428
   302 A      0.973*        1.479 +- 0.130
   303 S      0.929         1.442 +- 0.213
   314 A      0.503         0.990 +- 0.537
   316 I      0.948         1.457 +- 0.188
   318 T      0.937         1.449 +- 0.200
   319 A      0.876         1.395 +- 0.285
   321 A      0.793         1.310 +- 0.383
   324 S      0.922         1.434 +- 0.234
   327 T      0.563         1.055 +- 0.526
   637 T      0.830         1.350 +- 0.339
   638 V      0.960*        1.469 +- 0.155
   642 M      0.562         1.092 +- 0.478
   653 N      0.926         1.439 +- 0.221
   661 F      0.532         1.021 +- 0.532
   695 G      0.585         1.084 +- 0.514
   943 G      0.646         1.152 +- 0.487
   984 S      0.817         1.337 +- 0.352
  1002 A      0.525         1.034 +- 0.508
  1114 A      0.543         1.058 +- 0.500