--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Tue Nov 22 01:18:42 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/AcCoAS-PD/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6712.25         -6734.41
2      -6712.58         -6729.16
--------------------------------------
TOTAL    -6712.40         -6733.72
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/3/AcCoAS-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/AcCoAS-PD/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/AcCoAS-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.122917    0.004374    0.999246    1.253751    1.120666   1243.60   1326.39    1.000
r(A<->C){all}   0.098547    0.000178    0.073212    0.124985    0.098247   1160.25   1224.78    1.000
r(A<->G){all}   0.247285    0.000499    0.202732    0.290572    0.246776    792.37    832.68    1.001
r(A<->T){all}   0.097003    0.000311    0.063238    0.130673    0.096400    734.49    968.75    1.000
r(C<->G){all}   0.055660    0.000061    0.041805    0.071895    0.055304   1118.21   1129.79    1.001
r(C<->T){all}   0.434944    0.000637    0.383508    0.481242    0.435020    838.18    857.98    1.000
r(G<->T){all}   0.066561    0.000120    0.045318    0.087364    0.065886   1102.74   1132.16    1.002
pi(A){all}      0.210187    0.000077    0.193068    0.227262    0.209975   1033.01   1079.86    1.000
pi(C){all}      0.292864    0.000090    0.274577    0.311411    0.292768   1206.95   1274.11    1.000
pi(G){all}      0.289915    0.000093    0.271278    0.308780    0.289675   1122.85   1236.92    1.000
pi(T){all}      0.207034    0.000066    0.192026    0.223178    0.206837   1116.00   1224.99    1.000
alpha{1,2}      0.103149    0.000051    0.089704    0.116940    0.102932   1078.21   1181.94    1.000
alpha{3}        5.094502    1.187664    3.024922    7.181953    4.979400   1501.00   1501.00    1.000
pinvar{all}     0.409786    0.000654    0.361929    0.461384    0.410158   1306.07   1350.63    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	-6181.540846
Model 2: PositiveSelection	-6181.540848
Model 0: one-ratio	-6199.828236
Model 3: discrete	-6177.589209
Model 7: beta	-6181.121194
Model 8: beta&w>1	-6177.575576


Model 0 vs 1	36.57478000000083

Model 2 vs 1	3.99999953515362E-6

Model 8 vs 7	7.091236000000208

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_AcCoAS-PD)

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

   422 Y      0.501         1.211 +- 0.814