--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Dec 07 18:25:18 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/402/Spn-PD/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/402/Spn-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/402/Spn-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/402/Spn-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -23131.26        -23151.11
2     -23131.35        -23147.53
--------------------------------------
TOTAL   -23131.31        -23150.44
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/402/Spn-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/402/Spn-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/402/Spn-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}         1.185786    0.001592    1.111795    1.264950    1.184923   1451.84   1476.42    1.000
r(A<->C){all}   0.093680    0.000053    0.081264    0.109927    0.093578   1013.44   1063.79    1.000
r(A<->G){all}   0.232758    0.000134    0.211238    0.255549    0.232688    675.70    780.33    1.000
r(A<->T){all}   0.132533    0.000111    0.112894    0.153474    0.132485    746.21    841.19    1.001
r(C<->G){all}   0.071252    0.000026    0.061802    0.081338    0.071084    964.16   1034.11    1.000
r(C<->T){all}   0.400727    0.000201    0.373714    0.429046    0.400812    649.48    753.99    1.000
r(G<->T){all}   0.069049    0.000045    0.056181    0.081946    0.068837   1147.19   1189.92    1.000
pi(A){all}      0.227729    0.000023    0.218134    0.236857    0.227685    770.69    894.14    1.000
pi(C){all}      0.312521    0.000028    0.302352    0.322690    0.312433    840.09    939.19    1.000
pi(G){all}      0.301175    0.000027    0.291094    0.311041    0.301459    761.40    930.83    1.000
pi(T){all}      0.158575    0.000015    0.151241    0.166236    0.158547    929.85   1021.36    1.000
alpha{1,2}      0.126793    0.000030    0.116724    0.137941    0.126596   1174.96   1241.92    1.001
alpha{3}        5.347355    0.967240    3.552709    7.221855    5.229253   1173.91   1308.49    1.000
pinvar{all}     0.370139    0.000253    0.338655    0.401719    0.370462   1276.06   1327.66    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	-20230.015021
Model 2: PositiveSelection	-20230.015021
Model 0: one-ratio	-20634.81645
Model 3: discrete	-20202.114781
Model 7: beta	-20207.938984
Model 8: beta&w>1	-20203.0268


Model 0 vs 1	809.6028579999984

Model 2 vs 1	0.0

Model 8 vs 7	9.824368000001414

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_Spn-PD)

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

   143 I      0.766         1.282 +- 0.406
   149 V      0.586         1.081 +- 0.519
   167 Q      0.928         1.438 +- 0.226
   184 L      0.813         1.333 +- 0.357
   189 P      0.867         1.380 +- 0.313
   190 S      0.576         1.065 +- 0.527
   191 P      0.866         1.379 +- 0.315
   196 S      0.727         1.243 +- 0.432
   318 R      0.921         1.432 +- 0.239
   319 L      0.537         1.028 +- 0.530
   357 S      0.798         1.313 +- 0.383
   378 T      0.826         1.346 +- 0.344
   417 P      0.634         1.150 +- 0.475
   490 S      0.706         1.210 +- 0.465
   493 S      0.832         1.347 +- 0.350
   497 S      0.738         1.260 +- 0.414
   509 A      0.715         1.241 +- 0.422
   553 A      0.892         1.408 +- 0.269
   566 Q      0.582         1.101 +- 0.488
   567 T      0.829         1.345 +- 0.351
   643 S      0.742         1.246 +- 0.444
   645 S      0.625         1.142 +- 0.479
   647 L      0.519         1.027 +- 0.511
   701 L      0.583         1.075 +- 0.523
   809 S      0.593         1.086 +- 0.519
   810 I      0.974*        1.480 +- 0.127
   811 Q      0.853         1.368 +- 0.326
   814 T      0.837         1.352 +- 0.345
   922 F      0.845         1.363 +- 0.327
   935 A      0.514         1.021 +- 0.512
  1015 S      0.559         1.048 +- 0.529
  1016 S      0.908         1.422 +- 0.252
  1018 A      0.754         1.261 +- 0.433
  1019 P      0.741         1.246 +- 0.443
  1627 S      0.623         1.126 +- 0.499
  1632 V      0.563         1.077 +- 0.498
  1675 G      0.782         1.299 +- 0.392
  1709 T      0.552         1.043 +- 0.528
  1807 T      0.551         1.059 +- 0.507
  1844 S      0.925         1.438 +- 0.222