--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Nov 21 17:50:52 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/295/Lnk-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/295/Lnk-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/295/Lnk-PA/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/295/Lnk-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -8840.35         -8856.15
2      -8840.28         -8857.57
--------------------------------------
TOTAL    -8840.32         -8857.09
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/295/Lnk-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/295/Lnk-PA/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/295/Lnk-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.284705    0.004617    1.156776    1.421156    1.282137   1501.00   1501.00    1.000
r(A<->C){all}   0.106764    0.000122    0.084541    0.127284    0.106438   1104.97   1158.69    1.000
r(A<->G){all}   0.215512    0.000297    0.181407    0.247859    0.215202    784.46    916.38    1.000
r(A<->T){all}   0.124403    0.000221    0.096402    0.154537    0.123544    960.58   1026.03    1.000
r(C<->G){all}   0.074961    0.000067    0.059240    0.090318    0.074799   1057.26   1221.28    1.000
r(C<->T){all}   0.405653    0.000511    0.363822    0.452462    0.405706    619.16    831.55    1.000
r(G<->T){all}   0.072706    0.000106    0.053948    0.092929    0.072406   1069.72   1155.14    1.000
pi(A){all}      0.233749    0.000065    0.218423    0.249415    0.233731    916.11   1208.55    1.001
pi(C){all}      0.292704    0.000078    0.276392    0.311182    0.292598   1160.42   1177.72    1.000
pi(G){all}      0.296798    0.000082    0.280657    0.316429    0.296715    930.64   1004.97    1.000
pi(T){all}      0.176749    0.000050    0.162621    0.190314    0.176623    836.70   1056.13    1.000
alpha{1,2}      0.165202    0.000141    0.143230    0.188728    0.164777   1350.26   1406.98    1.003
alpha{3}        4.526188    0.881151    2.832990    6.324751    4.418485   1264.23   1380.02    1.000
pinvar{all}     0.367436    0.000634    0.318377    0.419257    0.367980   1038.18   1208.99    1.001
------------------------------------------------------------------------------------------------------
* 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	-7916.756018
Model 2: PositiveSelection	-7916.756039
Model 0: one-ratio	-7992.480109
Model 3: discrete	-7907.483779
Model 7: beta	-7913.023214
Model 8: beta&w>1	-7908.266947


Model 0 vs 1	151.4481820000001

Model 2 vs 1	4.199999966658652E-5

Model 8 vs 7	9.512533999999505

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_Lnk-PA)

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

    36 A      0.731         1.131
   323 S      0.940         1.372
   531 S      0.608         0.986
   543 N      0.932         1.362
   571 S      0.563         0.934
   576 T      0.700         1.094
   681 G      0.991**       1.429

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_Lnk-PA)

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

    36 A      0.804         1.325 +- 0.377
   323 S      0.918         1.436 +- 0.245
   531 S      0.770         1.282 +- 0.423
   543 N      0.917         1.434 +- 0.249
   571 S      0.741         1.252 +- 0.444
   576 T      0.790         1.310 +- 0.390
   681 G      0.972*        1.483 +- 0.150