--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Dec 07 19:29:07 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/408/Sur-8-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/408/Sur-8-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/408/Sur-8-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/408/Sur-8-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -7086.88         -7103.64
2      -7086.89         -7102.84
--------------------------------------
TOTAL    -7086.88         -7103.31
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/408/Sur-8-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/408/Sur-8-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/408/Sur-8-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}         1.195491    0.005079    1.064296    1.342105    1.193626   1277.79   1389.39    1.000
r(A<->C){all}   0.086150    0.000145    0.062349    0.109473    0.085834    723.27    875.01    1.000
r(A<->G){all}   0.231192    0.000430    0.186599    0.269271    0.231086    621.98    716.35    1.000
r(A<->T){all}   0.140227    0.000371    0.102731    0.176604    0.139750    729.80    791.61    1.000
r(C<->G){all}   0.047511    0.000049    0.034876    0.061441    0.047311   1101.71   1159.58    1.000
r(C<->T){all}   0.446736    0.000745    0.394032    0.501646    0.446119    795.43    862.46    1.000
r(G<->T){all}   0.048184    0.000093    0.029111    0.065893    0.047844    872.03   1113.43    1.000
pi(A){all}      0.237959    0.000085    0.220477    0.256198    0.237927   1019.93   1109.49    1.000
pi(C){all}      0.289033    0.000090    0.270218    0.306483    0.288774    953.35   1060.16    1.000
pi(G){all}      0.284400    0.000089    0.266388    0.303524    0.284420   1080.67   1172.01    1.000
pi(T){all}      0.188608    0.000062    0.174040    0.204384    0.188407   1112.96   1138.34    1.000
alpha{1,2}      0.146606    0.000139    0.124091    0.169705    0.146083   1266.42   1337.70    1.000
alpha{3}        4.122839    0.885541    2.367195    5.906466    4.033102   1289.17   1306.11    1.000
pinvar{all}     0.340675    0.000925    0.274959    0.396201    0.341613   1269.76   1339.72    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	-6163.564101
Model 2: PositiveSelection	-6163.564119
Model 0: one-ratio	-6268.228403
Model 3: discrete	-6157.426672
Model 7: beta	-6166.924836
Model 8: beta&w>1	-6157.495092


Model 0 vs 1	209.32860400000027

Model 2 vs 1	3.5999999454361387E-5

Model 8 vs 7	18.859488000000056

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_Sur-8-PA)

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

    38 S      0.751         0.785
    42 T      0.999**       1.005
    43 S      0.964*        0.974
    44 A      0.852         0.875
    47 P      0.973*        0.982
    53 G      0.808         0.836
    54 S      0.984*        0.992
    56 T      0.746         0.781
    61 A      0.997**       1.003
    62 G      0.592         0.644
    63 T      0.578         0.632
    67 S      0.979*        0.987
    69 A      0.792         0.822
    70 N      0.996**       1.003
    71 G      0.994**       1.001
    72 S      0.998**       1.005
    85 L      0.973*        0.982

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_Sur-8-PA)

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

    42 T      0.894         1.412 +- 0.275
    47 P      0.783         1.293 +- 0.414
    54 S      0.671         1.190 +- 0.460
    61 A      0.774         1.300 +- 0.386
    67 S      0.602         1.120 +- 0.486
    70 N      0.761         1.286 +- 0.398
    71 G      0.805         1.326 +- 0.370
    72 S      0.915         1.430 +- 0.250
    85 L      0.782         1.292 +- 0.414