--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Mon Dec 05 09:03:13 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/350/Pkn-PE/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/350/Pkn-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/350/Pkn-PE/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/350/Pkn-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6761.69         -6778.83
2      -6760.80         -6777.74
--------------------------------------
TOTAL    -6761.15         -6778.43
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/350/Pkn-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/350/Pkn-PE/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/350/Pkn-PE/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         1.057904    0.003594    0.943028    1.175255    1.055696   1365.55   1423.73    1.001
r(A<->C){all}   0.083318    0.000132    0.060290    0.104546    0.082755    923.17   1114.73    1.000
r(A<->G){all}   0.277002    0.000480    0.234627    0.319506    0.275883    988.21   1022.01    1.004
r(A<->T){all}   0.148755    0.000308    0.114760    0.182723    0.148384    781.44    905.34    1.000
r(C<->G){all}   0.050269    0.000059    0.035832    0.065323    0.049874   1209.44   1246.68    1.000
r(C<->T){all}   0.389272    0.000628    0.335872    0.435483    0.389254    922.04    931.62    1.004
r(G<->T){all}   0.051383    0.000088    0.033251    0.070083    0.050789   1132.30   1178.34    1.000
pi(A){all}      0.228662    0.000082    0.210762    0.246344    0.228515    895.90   1065.57    1.000
pi(C){all}      0.281043    0.000095    0.262156    0.299714    0.280979   1194.92   1200.92    1.000
pi(G){all}      0.276092    0.000094    0.257817    0.295327    0.275992   1041.33   1126.75    1.000
pi(T){all}      0.214203    0.000074    0.197583    0.231014    0.213786   1038.18   1187.47    1.001
alpha{1,2}      0.151569    0.000174    0.127558    0.178047    0.150792   1286.00   1374.13    1.000
alpha{3}        4.581619    1.131341    2.602327    6.568777    4.487124   1266.35   1329.56    1.000
pinvar{all}     0.345347    0.001007    0.281193    0.403622    0.346171   1171.45   1272.35    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	-6001.095042
Model 2: PositiveSelection	-6001.095042
Model 0: one-ratio	-6106.351862
Model 3: discrete	-5998.232592
Model 7: beta	-6003.463016
Model 8: beta&w>1	-5998.756002


Model 0 vs 1	210.51364000000103

Model 2 vs 1	0.0

Model 8 vs 7	9.414027999999234

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-PE)

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

    10 G      0.503         0.761
    25 T      0.969*        1.222
    29 Y      0.787         1.043
    40 Q      0.759         1.014
    42 L      0.544         0.796
    45 P      0.995**       1.248
    46 C      0.883         1.138
    48 V      0.956*        1.210
    49 P      0.502         0.754
    82 S      0.609         0.862
    91 E      0.649         0.906
    92 S      0.996**       1.249
    93 A      0.998**       1.251
    96 E      0.598         0.855
   131 S      0.779         1.036
   175 P      0.704         0.961
   229 T      0.556         0.813
   265 R      0.866         1.120

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-PE)

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

    25 T      0.904         1.422 +- 0.271
    29 Y      0.611         1.131 +- 0.483
    40 Q      0.656         1.161 +- 0.493
    45 P      0.956*        1.470 +- 0.182
    46 C      0.751         1.273 +- 0.416
    48 V      0.889         1.407 +- 0.294
    82 S      0.544         0.995 +- 0.583
    91 E      0.516         1.011 +- 0.531
    92 S      0.968*        1.480 +- 0.160
    93 A      0.974*        1.485 +- 0.144
   131 S      0.600         1.120 +- 0.486
   175 P      0.604         1.102 +- 0.517
   265 R      0.804         1.312 +- 0.410