--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Dec 05 04:19:59 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/350/Pkcdelta-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/350/Pkcdelta-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/350/Pkcdelta-PC/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/350/Pkcdelta-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6576.16         -6594.20
2      -6576.35         -6592.81
--------------------------------------
TOTAL    -6576.25         -6593.73
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/350/Pkcdelta-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/350/Pkcdelta-PC/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/350/Pkcdelta-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.851574    0.003041    0.746878    0.962022    0.851024   1341.74   1405.57    1.000
r(A<->C){all}   0.093314    0.000171    0.068801    0.120265    0.093133   1028.03   1035.11    1.000
r(A<->G){all}   0.254530    0.000558    0.209881    0.302913    0.254427    821.10    949.85    1.000
r(A<->T){all}   0.088546    0.000190    0.063376    0.117579    0.087851    856.52    879.03    1.000
r(C<->G){all}   0.069397    0.000098    0.050881    0.089748    0.069047    988.73   1022.93    1.000
r(C<->T){all}   0.442717    0.000734    0.386193    0.492736    0.442339    849.22    872.12    1.000
r(G<->T){all}   0.051495    0.000093    0.033570    0.070319    0.051022   1202.80   1223.95    1.000
pi(A){all}      0.249534    0.000083    0.231345    0.266925    0.249502   1036.03   1091.16    1.000
pi(C){all}      0.257269    0.000081    0.240337    0.274692    0.257102   1035.33   1046.45    1.000
pi(G){all}      0.266077    0.000087    0.247230    0.283970    0.265917   1058.32   1089.62    1.000
pi(T){all}      0.227119    0.000073    0.210650    0.244125    0.226949    904.23   1070.82    1.001
alpha{1,2}      0.144370    0.000152    0.120951    0.168798    0.143384   1335.18   1389.84    1.000
alpha{3}        4.374091    1.080205    2.541465    6.495915    4.268749   1237.55   1369.27    1.000
pinvar{all}     0.497714    0.000617    0.447697    0.544121    0.497918   1373.16   1407.25    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	-5982.71707
Model 2: PositiveSelection	-5982.717072
Model 0: one-ratio	-6011.633126
Model 3: discrete	-5975.812449
Model 7: beta	-5979.246239
Model 8: beta&w>1	-5976.0363


Model 0 vs 1	57.83211200000005

Model 2 vs 1	4.0000013541430235E-6

Model 8 vs 7	6.419878000000608

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_Pkcdelta-PC)

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

    96 V      0.935         1.709
    98 I      0.974*        1.771

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_Pkcdelta-PC)

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

    96 V      0.903         1.507 +- 0.461
    98 I      0.940         1.550 +- 0.451