--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu Nov 10 20:13:51 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/191/CG8312-PD/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/191/CG8312-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/191/CG8312-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/191/CG8312-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -9100.91         -9115.02
2      -9101.31         -9118.79
--------------------------------------
TOTAL    -9101.09         -9118.12
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/191/CG8312-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/191/CG8312-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/191/CG8312-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}         0.797077    0.001625    0.722786    0.878671    0.796476   1341.39   1413.75    1.000
r(A<->C){all}   0.085494    0.000107    0.064824    0.104911    0.085072    969.31   1013.03    1.000
r(A<->G){all}   0.191701    0.000281    0.159075    0.223364    0.191427    539.31    694.32    1.000
r(A<->T){all}   0.106973    0.000273    0.072901    0.137356    0.106186    860.64    890.34    1.000
r(C<->G){all}   0.071433    0.000058    0.056759    0.086149    0.071125   1033.79   1267.39    1.000
r(C<->T){all}   0.452768    0.000578    0.409154    0.502105    0.452253    480.84    697.16    1.000
r(G<->T){all}   0.091632    0.000139    0.069458    0.114947    0.091190    948.39   1023.22    1.000
pi(A){all}      0.243465    0.000063    0.227275    0.258086    0.243431    952.97    971.59    1.000
pi(C){all}      0.298010    0.000069    0.280605    0.313285    0.297862    952.51   1098.64    1.000
pi(G){all}      0.309037    0.000069    0.292199    0.324522    0.308945   1123.14   1201.38    1.000
pi(T){all}      0.149488    0.000038    0.137241    0.161231    0.149356    990.23   1009.51    1.000
alpha{1,2}      0.164367    0.000231    0.136108    0.194366    0.163483   1422.03   1426.49    1.000
alpha{3}        4.105226    1.014065    2.299863    6.057803    3.970267   1163.42   1264.19    1.000
pinvar{all}     0.326143    0.001158    0.262434    0.395479    0.327615    798.48   1040.58    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	-7979.277444
Model 2: PositiveSelection	-7979.277444
Model 0: one-ratio	-8091.814581
Model 3: discrete	-7953.774753
Model 7: beta	-7960.734676
Model 8: beta&w>1	-7954.139605


Model 0 vs 1	225.0742739999987

Model 2 vs 1	0.0

Model 8 vs 7	13.190141999999469

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_CG8312-PD)

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

     9 S      0.921         1.616
    13 D      0.996**       1.720
    48 V      0.758         1.388
    93 A      0.925         1.621
   587 T      0.767         1.403
   667 A      0.940         1.643
   831 T      0.596         1.164

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_CG8312-PD)

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

     9 S      0.934         1.448 +- 0.232
    13 D      0.981*        1.491 +- 0.128
    48 V      0.868         1.381 +- 0.334
    52 A      0.625         1.093 +- 0.556
    93 A      0.928         1.444 +- 0.234
    96 T      0.681         1.183 +- 0.490
    97 T      0.591         1.087 +- 0.522
    98 A      0.625         1.126 +- 0.509
   483 S      0.663         1.183 +- 0.465
   587 T      0.851         1.374 +- 0.325
   634 T      0.526         1.037 +- 0.511
   667 A      0.926         1.444 +- 0.231
   831 T      0.775         1.301 +- 0.390
   832 S      0.730         1.216 +- 0.497