--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Thu Nov 24 20:49:31 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/320/Ncc69-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/320/Ncc69-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/320/Ncc69-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/320/Ncc69-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -13823.70        -13839.66
2     -13822.98        -13839.00
--------------------------------------
TOTAL   -13823.28        -13839.38
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/320/Ncc69-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/320/Ncc69-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/320/Ncc69-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}         1.214959    0.002486    1.120996    1.312710    1.214481   1322.28   1348.94    1.000
r(A<->C){all}   0.108445    0.000101    0.089141    0.128172    0.107962   1020.99   1069.59    1.001
r(A<->G){all}   0.222412    0.000211    0.195315    0.250540    0.222439    802.18    868.44    1.000
r(A<->T){all}   0.111026    0.000138    0.089320    0.134261    0.110609    906.40   1031.49    1.000
r(C<->G){all}   0.083203    0.000048    0.069883    0.097102    0.082936    914.41   1017.00    1.000
r(C<->T){all}   0.417196    0.000308    0.382144    0.449443    0.417103    692.28    749.67    1.000
r(G<->T){all}   0.057718    0.000046    0.045084    0.071748    0.057401   1151.39   1160.80    1.000
pi(A){all}      0.213314    0.000042    0.200897    0.226007    0.213223    822.89    846.30    1.000
pi(C){all}      0.283460    0.000048    0.270387    0.296953    0.283426    911.40    930.11    1.000
pi(G){all}      0.285503    0.000051    0.271945    0.299224    0.285564    966.71    986.99    1.000
pi(T){all}      0.217723    0.000038    0.205549    0.229240    0.217595    803.37    865.94    1.000
alpha{1,2}      0.149511    0.000069    0.132493    0.165355    0.149458   1283.08   1346.98    1.000
alpha{3}        4.618395    0.823988    3.029605    6.510589    4.514315   1197.23   1331.23    1.000
pinvar{all}     0.358943    0.000459    0.316354    0.398869    0.358808   1246.31   1249.55    1.001
------------------------------------------------------------------------------------------------------
* 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	-12837.484247
Model 2: PositiveSelection	-12837.484256
Model 0: one-ratio	-13006.984516
Model 3: discrete	-12792.236775
Model 7: beta	-12810.637666
Model 8: beta&w>1	-12793.530163


Model 0 vs 1	339.00053800000023

Model 2 vs 1	1.799999881768599E-5

Model 8 vs 7	34.21500600000218

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_Ncc69-PC)

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

    35 A      0.929         1.765
    38 P      0.961*        1.817
    44 A      0.986*        1.857
    46 A      0.843         1.627
    47 G      0.665         1.343
    48 A      0.983*        1.852
    49 G      0.521         1.112
    50 A      0.986*        1.856
    52 A      1.000**       1.879
   388 A      0.850         1.639
   449 Q      0.858         1.651
   487 S      0.785         1.535
   861 V      0.845         1.631

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_Ncc69-PC)

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

    35 A      0.880         1.417 +- 0.317
    38 P      0.932         1.464 +- 0.271
    44 A      0.949         1.481 +- 0.240
    46 A      0.854         1.388 +- 0.361
    47 G      0.777         1.302 +- 0.443
    48 A      0.951*        1.482 +- 0.240
    49 G      0.704         1.223 +- 0.488
    50 A      0.954*        1.485 +- 0.234
    52 A      0.994**       1.519 +- 0.162
   388 A      0.844         1.380 +- 0.360
   449 Q      0.863         1.397 +- 0.353
   487 S      0.824         1.358 +- 0.390
   489 V      0.666         1.192 +- 0.480
   505 N      0.568         1.089 +- 0.504
   861 V      0.840         1.377 +- 0.364