--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Sep 29 05:24:47 WEST 2017
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/ADOPS1/ASP1/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/ASP1/ClustalW2/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/ASP1/ClustalW2/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/ADOPS1/ASP1/ClustalW2/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -11375.06        -11433.98
2     -11374.67        -11436.60
--------------------------------------
TOTAL   -11374.84        -11435.98
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/ASP1/ClustalW2/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/ASP1/ClustalW2/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/ADOPS1/ASP1/ClustalW2/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}        15.989573    0.778511   14.342760   17.763120   15.982220    644.77    710.78    1.000
r(A<->C){all}   0.065064    0.000079    0.047897    0.081700    0.064687    247.02    347.70    1.000
r(A<->G){all}   0.288662    0.000528    0.247687    0.339218    0.287788    122.14    148.37    1.000
r(A<->T){all}   0.079213    0.000072    0.062098    0.095351    0.078794    198.38    345.14    1.000
r(C<->G){all}   0.069071    0.000103    0.050607    0.089123    0.068486    338.57    423.25    1.001
r(C<->T){all}   0.320775    0.000556    0.272428    0.365624    0.320839    104.38    130.91    1.000
r(G<->T){all}   0.177214    0.000212    0.149051    0.205834    0.176951    353.13    365.46    1.000
pi(A){all}      0.217401    0.000162    0.191721    0.241587    0.217229    248.91    261.42    1.000
pi(C){all}      0.264986    0.000123    0.243987    0.287186    0.265164    210.22    278.47    1.000
pi(G){all}      0.158398    0.000125    0.136733    0.179248    0.158176    124.32    168.58    1.000
pi(T){all}      0.359215    0.000180    0.333236    0.385040    0.358817    195.03    212.64    1.000
alpha{1,2}      0.544395    0.001351    0.474182    0.617942    0.544140    881.23   1035.37    1.000
alpha{3}        0.669775    0.002347    0.569779    0.761964    0.668596    688.51    858.56    1.001
pinvar{all}     0.338157    0.000551    0.290867    0.381309    0.338230    802.41    965.66    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	-6337.020012
Model 2: PositiveSelection	-6228.794468
Model 0: one-ratio	-6683.0048
Model 3: discrete	-6226.583334
Model 7: beta	-6333.602326
Model 8: beta&w>1	-6221.989614


Model 0 vs 1	691.9695759999995

Model 2 vs 1	216.4510879999998

Additional information for M1 vs M2:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: 01_AE.AF.07.569M.GQ477441)

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

     9 I      1.000**       4.356
   103 S      0.999**       4.353
   107 P      1.000**       4.356
   119 T      1.000**       4.356
   120 Q      0.998**       4.349
   123 I      1.000**       4.356
   125 L      0.999**       4.354
   135 A      1.000**       4.356
   151 S      0.827         3.777

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: 01_AE.AF.07.569M.GQ477441)

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

     9 I      1.000**       4.499 +- 0.233
   103 S      0.999**       4.494 +- 0.268
   107 P      1.000**       4.499 +- 0.233
   119 T      1.000**       4.499 +- 0.233
   120 Q      0.998**       4.491 +- 0.291
   123 I      1.000**       4.499 +- 0.233
   125 L      0.999**       4.497 +- 0.251
   135 A      0.999**       4.497 +- 0.246
   151 S      0.757         3.625 +- 1.497


Model 8 vs 7	223.2254240000002

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: 01_AE.AF.07.569M.GQ477441)

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

     9 I      1.000**       3.920
   103 S      1.000**       3.919
   107 P      1.000**       3.920
   119 T      1.000**       3.920
   120 Q      0.999**       3.917
   123 I      1.000**       3.920
   125 L      1.000**       3.918
   135 A      1.000**       3.919
   141 I      0.548         2.550
   151 S      0.950*        3.769

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: 01_AE.AF.07.569M.GQ477441)

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

     9 I      1.000**       4.097 +- 0.494
   103 S      0.999**       4.092 +- 0.508
   107 P      1.000**       4.097 +- 0.494
   119 T      1.000**       4.097 +- 0.494
   120 Q      0.998**       4.089 +- 0.518
   123 I      1.000**       4.097 +- 0.494
   125 L      0.999**       4.094 +- 0.502
   135 A      0.999**       4.095 +- 0.500
   151 S      0.688         2.997 +- 1.446