--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Dec 10 21:27:39 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-PH/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -19380.07        -19399.32
2     -19380.42        -19400.77
--------------------------------------
TOTAL   -19380.23        -19400.28
--------------------------------------


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

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.211332    0.001611    1.134579    1.293458    1.211003   1305.65   1403.33    1.001
r(A<->C){all}   0.058158    0.000030    0.047931    0.069094    0.058104    778.41    981.08    1.000
r(A<->G){all}   0.285992    0.000172    0.260138    0.310712    0.286199    719.75    802.29    1.003
r(A<->T){all}   0.096730    0.000099    0.077700    0.115973    0.096287    712.68    783.17    1.000
r(C<->G){all}   0.026110    0.000008    0.020500    0.031592    0.026004   1213.40   1224.89    1.000
r(C<->T){all}   0.484404    0.000248    0.453377    0.515234    0.484341    675.31    792.00    1.002
r(G<->T){all}   0.048606    0.000031    0.037397    0.059052    0.048440    925.63   1024.82    1.000
pi(A){all}      0.268829    0.000029    0.257974    0.279492    0.268718    978.59   1003.26    1.001
pi(C){all}      0.261372    0.000028    0.250532    0.271390    0.261320   1078.29   1078.74    1.002
pi(G){all}      0.302611    0.000031    0.291892    0.313876    0.302575    996.22   1111.90    1.000
pi(T){all}      0.167187    0.000019    0.158433    0.175262    0.167295    949.06    987.42    1.000
alpha{1,2}      0.087132    0.000015    0.079617    0.094439    0.087022   1077.19   1244.14    1.000
alpha{3}        8.214051    1.845854    5.744881   10.986490    8.080991   1410.56   1425.00    1.000
pinvar{all}     0.397966    0.000203    0.371680    0.426845    0.397790   1305.93   1333.21    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	-17880.438935
Model 2: PositiveSelection	-17800.501434
Model 0: one-ratio	-17826.577534
Model 3: discrete	-17784.39425
Model 7: beta	-17793.513361
Model 8: beta&w>1	-17791.303047


Model 0 vs 1	107.72280199999659

Model 2 vs 1	159.8750019999934

Additional information for M1 vs M2:
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-PH)

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



Model 8 vs 7	4.4206279999998515