--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sun Dec 04 14:42:27 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/351/Pkn-PK/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/351/Pkn-PK/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/351/Pkn-PK/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/351/Pkn-PK/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -15191.84        -15207.87
2     -15191.73        -15208.02
--------------------------------------
TOTAL   -15191.79        -15207.95
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/351/Pkn-PK/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/351/Pkn-PK/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/351/Pkn-PK/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.082362    0.001600    1.005913    1.159620    1.082031   1387.92   1444.46    1.000
r(A<->C){all}   0.105026    0.000076    0.087275    0.121358    0.104553    885.20    947.52    1.000
r(A<->G){all}   0.284141    0.000199    0.258174    0.313312    0.283640    930.69   1036.46    1.000
r(A<->T){all}   0.110143    0.000116    0.090200    0.132337    0.110047    957.39    965.23    1.000
r(C<->G){all}   0.052019    0.000027    0.042276    0.062205    0.051882    866.76   1047.87    1.000
r(C<->T){all}   0.386952    0.000259    0.356076    0.419206    0.386530    825.50    866.39    1.000
r(G<->T){all}   0.061719    0.000043    0.049052    0.074385    0.061426   1123.89   1144.61    1.000
pi(A){all}      0.230954    0.000038    0.219017    0.242879    0.230781    836.31    855.31    1.001
pi(C){all}      0.274221    0.000040    0.261552    0.286440    0.274088   1028.27   1093.56    1.000
pi(G){all}      0.298420    0.000044    0.285912    0.311272    0.298501   1039.51   1043.45    1.001
pi(T){all}      0.196405    0.000030    0.185123    0.206419    0.196485    942.45   1043.83    1.000
alpha{1,2}      0.137292    0.000057    0.122655    0.152181    0.136985   1272.33   1386.66    1.000
alpha{3}        6.004522    1.366968    3.875579    8.301270    5.845014   1369.67   1392.28    1.000
pinvar{all}     0.339402    0.000426    0.298993    0.378911    0.340118   1081.95   1146.18    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	-13983.905481
Model 2: PositiveSelection	-13983.905884
Model 0: one-ratio	-14182.075663
Model 3: discrete	-13970.417068
Model 7: beta	-13975.883712
Model 8: beta&w>1	-13971.558664


Model 0 vs 1	396.3403639999997

Model 2 vs 1	8.060000000114087E-4

Model 8 vs 7	8.650096000001213

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_Pkn-PK)

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

    28 A      0.866         1.277
    33 I      0.866         1.276
    35 R      0.827         1.235
    75 F      0.900         1.312
    78 E      0.741         1.146
   447 I      0.557         0.952
   859 S      0.960*        1.375
   860 A      0.966*        1.380

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_Pkn-PK)

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

    28 A      0.929         1.440 +- 0.221
    33 I      0.929         1.441 +- 0.221
    34 A      0.607         1.103 +- 0.512
    35 R      0.906         1.420 +- 0.253
    47 R      0.537         1.026 +- 0.532
    50 T      0.536         1.050 +- 0.503
    72 S      0.546         1.036 +- 0.530
    73 Y      0.525         1.010 +- 0.537
    75 F      0.944         1.453 +- 0.196
    76 D      0.536         1.048 +- 0.504
    78 E      0.874         1.390 +- 0.296
   230 N      0.522         1.036 +- 0.504
   237 A      0.779         1.287 +- 0.413
   418 Q      0.501         0.939 +- 0.589
   447 I      0.823         1.329 +- 0.381
   673 L      0.743         1.261 +- 0.418
   676 S      0.595         1.109 +- 0.491
   783 S      0.508         0.994 +- 0.537
   809 T      0.606         1.103 +- 0.512
   849 S      0.520         0.963 +- 0.585
   859 S      0.970*        1.476 +- 0.139
   860 A      0.968*        1.475 +- 0.142
  1031 R      0.696         1.182 +- 0.499