--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Tue Dec 06 18:27:23 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/388/sfl-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/388/sfl-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/388/sfl-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/388/sfl-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -11228.89        -11246.69
2     -11228.81        -11243.91
--------------------------------------
TOTAL   -11228.85        -11246.06
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/388/sfl-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/388/sfl-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/388/sfl-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}         1.098207    0.002980    0.996642    1.206920    1.096194   1247.13   1374.06    1.000
r(A<->C){all}   0.119375    0.000141    0.096910    0.143032    0.119190   1075.79   1126.78    1.000
r(A<->G){all}   0.249894    0.000296    0.216624    0.283574    0.250062    816.64    862.30    1.000
r(A<->T){all}   0.084077    0.000129    0.062697    0.106931    0.083868    935.69   1032.37    1.000
r(C<->G){all}   0.084701    0.000078    0.067264    0.101552    0.084429   1021.12   1153.78    1.000
r(C<->T){all}   0.395226    0.000397    0.357248    0.435318    0.394889    670.32    673.28    1.000
r(G<->T){all}   0.066728    0.000073    0.050506    0.083309    0.066352   1103.60   1149.05    1.000
pi(A){all}      0.236043    0.000051    0.222470    0.249869    0.235969    923.83    963.02    1.001
pi(C){all}      0.271053    0.000050    0.257264    0.284845    0.270925   1019.98   1101.26    1.001
pi(G){all}      0.270379    0.000051    0.256166    0.284631    0.270339   1251.15   1273.45    1.000
pi(T){all}      0.222525    0.000043    0.209456    0.235129    0.222402    845.60    870.72    1.000
alpha{1,2}      0.141202    0.000087    0.123638    0.159293    0.140781   1365.08   1366.94    1.000
alpha{3}        3.866371    0.707907    2.456195    5.640835    3.751284   1284.53   1338.64    1.000
pinvar{all}     0.465467    0.000419    0.426562    0.506790    0.465872   1247.31   1337.81    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	-9959.628132
Model 2: PositiveSelection	-9959.628132
Model 0: one-ratio	-10105.714737
Model 3: discrete	-9948.386509
Model 7: beta	-9957.485486
Model 8: beta&w>1	-9948.729368


Model 0 vs 1	292.17321000000084

Model 2 vs 1	0.0

Model 8 vs 7	17.512235999998666

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_sfl-PA)

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

    38 C      0.936         1.062
    45 Q      0.972*        1.095
    68 R      0.881         1.013
    93 N      0.995**       1.116
    94 G      0.999**       1.119
   116 T      0.936         1.062
   119 A      0.727         0.873
   120 S      0.970*        1.093
   123 G      0.723         0.870
   126 P      0.805         0.944
   127 A      0.724         0.871
   336 L      0.853         0.987

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_sfl-PA)

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

    38 C      0.784         1.307 +- 0.377
    45 Q      0.868         1.387 +- 0.298
    68 R      0.777         1.294 +- 0.396
    93 N      0.939         1.451 +- 0.198
    94 G      0.982*        1.486 +- 0.105
   116 T      0.790         1.313 +- 0.373
   119 A      0.667         1.171 +- 0.483
   120 S      0.890         1.406 +- 0.276
   123 G      0.541         1.055 +- 0.501
   126 P      0.770         1.277 +- 0.421
   127 A      0.560         1.074 +- 0.499
   336 L      0.730         1.248 +- 0.427