--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Nov 21 18:32:44 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/3/ACC-PE/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/3/ACC-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/ACC-PE/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/3/ACC-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -25900.73        -25919.20
2     -25900.86        -25919.23
--------------------------------------
TOTAL   -25900.80        -25919.21
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/3/ACC-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/ACC-PE/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/3/ACC-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.469208    0.001564    1.393113    1.546618    1.468443   1296.69   1398.85    1.000
r(A<->C){all}   0.086571    0.000040    0.074648    0.099672    0.086339   1082.06   1167.16    1.001
r(A<->G){all}   0.306117    0.000128    0.283874    0.327483    0.306194    659.97    727.54    1.000
r(A<->T){all}   0.110999    0.000076    0.094580    0.128030    0.110920    786.21    953.41    1.000
r(C<->G){all}   0.043109    0.000012    0.035911    0.049595    0.043026   1013.70   1066.71    1.000
r(C<->T){all}   0.390431    0.000157    0.364802    0.413477    0.390116    540.44    635.69    1.000
r(G<->T){all}   0.062772    0.000026    0.053416    0.073093    0.062622   1138.45   1150.33    1.000
pi(A){all}      0.211857    0.000021    0.203454    0.221354    0.211881    716.30    801.56    1.000
pi(C){all}      0.289466    0.000024    0.280254    0.299623    0.289494    775.82    933.55    1.000
pi(G){all}      0.284968    0.000025    0.274770    0.294314    0.284809    890.04    959.48    1.001
pi(T){all}      0.213710    0.000018    0.205380    0.221735    0.213677    873.32    960.97    1.000
alpha{1,2}      0.093228    0.000011    0.086717    0.099511    0.093197   1429.24   1462.50    1.000
alpha{3}        7.683376    1.533677    5.530382   10.272480    7.558732   1306.52   1403.76    1.000
pinvar{all}     0.300099    0.000192    0.274347    0.327793    0.300152   1181.99   1288.88    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	-23667.82825
Model 2: PositiveSelection	-23667.828253
Model 0: one-ratio	-23866.748102
Model 3: discrete	-23637.964041
Model 7: beta	-23659.21251
Model 8: beta&w>1	-23642.955823


Model 0 vs 1	397.83970400000544

Model 2 vs 1	6.000002031214535E-6

Model 8 vs 7	32.51337400000193

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_ACC-PE)

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

    29 A      0.964*        1.472 +- 0.155
    60 S      0.555         1.068 +- 0.501
    61 S      0.632         1.165 +- 0.453
    63 Q      0.864         1.384 +- 0.300
   293 N      0.592         1.131 +- 0.459
   765 S      0.833         1.356 +- 0.331
   828 L      0.661         1.179 +- 0.463
  2149 A      0.602         1.116 +- 0.489