--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Nov 07 10:38:53 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/161/CG46244-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/161/CG46244-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/161/CG46244-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/161/CG46244-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1       -146.62          -158.03
2       -146.29          -159.66
--------------------------------------
TOTAL     -146.44          -159.15
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/161/CG46244-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/161/CG46244-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/161/CG46244-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}         1.935610    0.198518    1.111090    2.837366    1.903942   1014.70   1156.25    1.000
r(A<->C){all}   0.108573    0.011164    0.000001    0.306852    0.078195    296.03    358.02    1.001
r(A<->G){all}   0.236642    0.027127    0.000356    0.546968    0.207967    209.51    223.41    1.000
r(A<->T){all}   0.042910    0.002608    0.000012    0.146012    0.025807    318.14    466.27    1.003
r(C<->G){all}   0.139977    0.017977    0.000027    0.408171    0.099930    155.84    158.35    1.002
r(C<->T){all}   0.300297    0.030618    0.029522    0.652046    0.272245    113.00    129.07    1.005
r(G<->T){all}   0.171602    0.018371    0.000343    0.438034    0.139495    266.37    294.52    1.006
pi(A){all}      0.303991    0.002556    0.204507    0.400660    0.303246    991.79   1131.80    1.000
pi(C){all}      0.173664    0.001569    0.094457    0.245215    0.170129   1091.75   1120.09    1.001
pi(G){all}      0.180034    0.001702    0.102256    0.258420    0.177207   1079.36   1244.71    1.001
pi(T){all}      0.342310    0.002720    0.243510    0.445177    0.340408   1168.26   1218.77    1.000
alpha{1,2}      0.314421    0.089594    0.004390    0.904983    0.212644   1255.95   1326.59    1.000
alpha{3}        0.357305    0.086089    0.049131    0.916327    0.270757   1394.33   1394.48    1.000
pinvar{all}     0.866638    0.004713    0.734314    0.970401    0.879896   1155.91   1199.63    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	-166.133028
Model 2: PositiveSelection	-154.776127
Model 0: one-ratio	-175.373989
Model 3: discrete	-154.776127
Model 7: beta	-166.137368
Model 8: beta&w>1	-154.776122


Model 0 vs 1	18.481921999999997

Model 2 vs 1	22.713801999999987

Additional information for M1 vs M2:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: D_melanogaster_CG46244-PA)

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

     9 H      1.000**       47.379
    19 S      1.000**       47.379

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_CG46244-PA)

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

     9 H      0.988*        9.485 +- 1.505
    19 S      1.000**       9.588 +- 1.172


Model 8 vs 7	22.722492000000045

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_CG46244-PA)

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

     9 H      1.000**       47.379
    19 S      1.000**       47.379

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_CG46244-PA)

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

     9 H      0.995**       9.545 +- 1.328
    19 S      1.000**       9.589 +- 1.172