--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Dec 10 14:46:23 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/443/zip-PB/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/443/zip-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/443/zip-PB/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/443/zip-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -20054.15        -20071.74
2     -20053.53        -20072.46
--------------------------------------
TOTAL   -20053.80        -20072.16
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/443/zip-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/443/zip-PB/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/443/zip-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.191087    0.001494    1.117823    1.268381    1.190799   1425.63   1463.32    1.000
r(A<->C){all}   0.058392    0.000028    0.048330    0.068887    0.058288   1007.61   1043.48    1.000
r(A<->G){all}   0.282281    0.000164    0.258424    0.307647    0.282023    901.50    985.42    1.002
r(A<->T){all}   0.099060    0.000093    0.081221    0.117607    0.098877    802.12    849.16    1.001
r(C<->G){all}   0.027273    0.000009    0.021091    0.032441    0.027233   1020.01   1184.69    1.000
r(C<->T){all}   0.483409    0.000233    0.453215    0.512991    0.482915    875.37    879.38    1.001
r(G<->T){all}   0.049585    0.000030    0.037930    0.059112    0.049479    900.66   1033.21    1.001
pi(A){all}      0.269830    0.000028    0.259703    0.280060    0.269700   1001.07   1060.27    1.000
pi(C){all}      0.259302    0.000026    0.248543    0.268643    0.259425    941.13   1056.32    1.000
pi(G){all}      0.303472    0.000029    0.292770    0.313928    0.303443    987.15   1048.44    1.000
pi(T){all}      0.167396    0.000018    0.159103    0.175941    0.167349   1024.46   1149.93    1.000
alpha{1,2}      0.092748    0.000016    0.084909    0.100503    0.092657    938.39   1219.69    1.000
alpha{3}        8.125717    1.845392    5.672094   10.830730    8.010053   1463.10   1482.05    1.000
pinvar{all}     0.389802    0.000209    0.362251    0.418552    0.390044   1394.79   1447.90    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	-18474.904665
Model 2: PositiveSelection	-18474.904793
Model 0: one-ratio	-18554.721333
Model 3: discrete	-18456.909011
Model 7: beta	-18473.052494
Model 8: beta&w>1	-18459.064533


Model 0 vs 1	159.63333600000624

Model 2 vs 1	2.5600000662961975E-4

Model 8 vs 7	27.97592199999781

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_zip-PB)

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

   235 N      0.713         1.229 +- 0.472
   254 N      0.813         1.348 +- 0.365
   255 C      0.796         1.318 +- 0.423
  1656 S      0.503         0.947 +- 0.601
  1877 L      0.516         1.007 +- 0.542
  1988 A      0.870         1.399 +- 0.338