--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 11 00:23:15 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/186/CG7766-PI/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/186/CG7766-PI/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/186/CG7766-PI/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/186/CG7766-PI/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -11539.43        -11554.18
2     -11539.66        -11555.75
--------------------------------------
TOTAL   -11539.54        -11555.25
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/186/CG7766-PI/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/186/CG7766-PI/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/186/CG7766-PI/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.067379    0.002614    0.966162    1.163345    1.065976   1254.09   1275.43    1.000
r(A<->C){all}   0.068732    0.000079    0.051549    0.085469    0.068382    952.67   1002.10    1.000
r(A<->G){all}   0.264734    0.000346    0.228525    0.300109    0.264395    808.69    895.02    1.001
r(A<->T){all}   0.081366    0.000223    0.052348    0.109316    0.080950    892.00    918.53    1.000
r(C<->G){all}   0.083404    0.000053    0.070788    0.099021    0.083396    911.27   1056.27    1.000
r(C<->T){all}   0.447695    0.000474    0.406903    0.489943    0.447763    741.45    796.60    1.001
r(G<->T){all}   0.054068    0.000073    0.038209    0.071405    0.053799   1023.34   1189.11    1.000
pi(A){all}      0.204385    0.000041    0.191904    0.216717    0.204396    966.66    986.85    1.001
pi(C){all}      0.314901    0.000048    0.301670    0.327894    0.314933   1122.40   1172.96    1.000
pi(G){all}      0.297791    0.000051    0.283613    0.311697    0.297620   1174.71   1218.66    1.000
pi(T){all}      0.182923    0.000035    0.172221    0.195143    0.182778    987.58   1118.99    1.000
alpha{1,2}      0.090361    0.000032    0.079550    0.101712    0.090096   1122.64   1221.85    1.000
alpha{3}        5.252143    1.120007    3.450028    7.374641    5.146481   1501.00   1501.00    1.000
pinvar{all}     0.464053    0.000328    0.429534    0.499126    0.464710   1089.45   1130.10    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	-10459.356263
Model 2: PositiveSelection	-10459.356296
Model 0: one-ratio	-10499.099989
Model 3: discrete	-10455.540937
Model 7: beta	-10471.433477
Model 8: beta&w>1	-10458.925832


Model 0 vs 1	79.48745200000121

Model 2 vs 1	6.600000051548705E-5

Model 8 vs 7	25.015289999999368

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_CG7766-PI)

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