--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Nov 21 16:35:44 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/3/ACC-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/3/ACC-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/ACC-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/3/ACC-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -26623.68        -26641.93
2     -26623.79        -26642.60
--------------------------------------
TOTAL   -26623.73        -26642.32
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/3/ACC-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/ACC-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/3/ACC-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}         1.573264    0.001804    1.495471    1.659774    1.572764   1354.62   1356.66    1.000
r(A<->C){all}   0.082248    0.000034    0.070621    0.093093    0.082331    879.11   1009.85    1.000
r(A<->G){all}   0.313411    0.000132    0.290646    0.335403    0.313446    767.11    920.42    1.000
r(A<->T){all}   0.113105    0.000075    0.096776    0.130174    0.113066    642.98    772.00    1.000
r(C<->G){all}   0.042181    0.000011    0.035286    0.048481    0.042094    959.19   1042.12    1.000
r(C<->T){all}   0.385873    0.000146    0.362370    0.410283    0.385761    678.31    699.49    1.000
r(G<->T){all}   0.063181    0.000024    0.053665    0.072696    0.063027    972.68   1011.42    1.000
pi(A){all}      0.211309    0.000022    0.202558    0.220713    0.211353    873.30    942.37    1.000
pi(C){all}      0.290136    0.000022    0.280997    0.299088    0.290063   1043.83   1177.90    1.000
pi(G){all}      0.284877    0.000024    0.275321    0.294607    0.284679    870.20    904.41    1.001
pi(T){all}      0.213678    0.000019    0.205192    0.222091    0.213596    531.25    806.71    1.002
alpha{1,2}      0.091149    0.000010    0.085312    0.097479    0.091061   1385.04   1443.02    1.000
alpha{3}        7.809226    1.477869    5.665973   10.377980    7.690800   1313.49   1397.25    1.000
pinvar{all}     0.292115    0.000180    0.265606    0.318286    0.292330   1086.92   1188.77    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	-24565.669304
Model 2: PositiveSelection	-24565.669356
Model 0: one-ratio	-24706.841833
Model 3: discrete	-24514.70771
Model 7: beta	-24531.162641
Model 8: beta&w>1	-24523.020789


Model 0 vs 1	282.34505799999897

Model 2 vs 1	1.0399999882793054E-4

Model 8 vs 7	16.283704000001308

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_ACC-PC)

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

   280 N      0.655         1.196 +- 0.433
   752 S      0.734         1.265 +- 0.410
   757 Y      0.563         1.079 +- 0.499
   815 L      0.692         1.220 +- 0.437
  2136 A      0.515         1.026 +- 0.510