--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sun Oct 29 09:29:11 WET 2017
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=MUSCLE
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=/usr/bin/
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb
tcoffee.bin=t_coffee
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/Ebola_B1_2/sGP/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/Ebola_B1_2/sGP/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Ebola_B1_2/sGP/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/Ebola_B1_2/sGP/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -8330.76         -8402.91
2      -8335.96         -8407.55
--------------------------------------
TOTAL    -8331.44         -8406.87
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/Ebola_B1_2/sGP/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Ebola_B1_2/sGP/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/Ebola_B1_2/sGP/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         8.608120    0.460246    7.304150    9.926875    8.570832    158.23    162.82    1.002
r(A<->C){all}   0.191407    0.000227    0.161666    0.219819    0.191166    876.71    903.04    1.000
r(A<->G){all}   0.296941    0.000381    0.258049    0.334413    0.296476    615.83    640.61    1.000
r(A<->T){all}   0.075491    0.000137    0.054840    0.099915    0.075126    737.18    749.74    1.003
r(C<->G){all}   0.047902    0.000123    0.027477    0.070417    0.047465    774.08    785.13    1.000
r(C<->T){all}   0.318411    0.000406    0.278657    0.358112    0.317780    548.45    605.29    1.000
r(G<->T){all}   0.069848    0.000127    0.047812    0.091086    0.069591    737.77    826.14    1.000
pi(A){all}      0.293577    0.000070    0.277855    0.310461    0.293453    926.39    928.09    1.000
pi(C){all}      0.260663    0.000064    0.244192    0.275796    0.260707    775.20    828.39    1.000
pi(G){all}      0.216660    0.000065    0.201384    0.232163    0.216787    521.63    663.18    1.000
pi(T){all}      0.229100    0.000067    0.213663    0.244731    0.229107    813.98    855.69    1.000
alpha{1,2}      0.565982    0.002023    0.476844    0.649458    0.564702    737.79    794.21    1.001
alpha{3}        4.596379    0.955027    2.806196    6.528917    4.471579    814.50   1087.29    1.001
pinvar{all}     0.008384    0.000048    0.000001    0.021935    0.006692    871.69    971.60    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	-5549.145913
Model 2: PositiveSelection	-5501.516922
Model 0: one-ratio	-5624.826672
Model 3: discrete	-5485.762566
Model 7: beta	-5566.323159
Model 8: beta&w>1	-5497.630372


Model 0 vs 1	151.3615179999997

Model 2 vs 1	95.257982000001

Additional information for M1 vs M2:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: gb:KF827427|Organism:Zaire ebolavirus|Strain Name:rec/COD/1976/Mayinga-rgEBOV|Protein Name:sGP|Gene Symbol:GP)

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

   276 T      1.000**       26.512
   277 S      1.000**       26.512

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: gb:KF827427|Organism:Zaire ebolavirus|Strain Name:rec/COD/1976/Mayinga-rgEBOV|Protein Name:sGP|Gene Symbol:GP)

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

   276 T      1.000**       10.303 +- 0.461
   277 S      1.000**       10.303 +- 0.461


Model 8 vs 7	137.3855739999999

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: gb:KF827427|Organism:Zaire ebolavirus|Strain Name:rec/COD/1976/Mayinga-rgEBOV|Protein Name:sGP|Gene Symbol:GP)

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

   276 T      1.000**       22.605
   277 S      1.000**       22.605

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: gb:KF827427|Organism:Zaire ebolavirus|Strain Name:rec/COD/1976/Mayinga-rgEBOV|Protein Name:sGP|Gene Symbol:GP)

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

   276 T      1.000**       10.280 +- 0.488
   277 S      1.000**       10.280 +- 0.488