--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sun Nov 05 00:13:54 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=
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/Ebolaaminoresults/sGP/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -7937.55         -7982.36
2      -7934.99         -7989.37
--------------------------------------
TOTAL    -7935.61         -7988.68
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/Ebolaaminoresults/sGP/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Ebolaaminoresults/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/ADOPS1/Ebolaaminoresults/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}         7.549318    0.373186    6.355003    8.712142    7.532367    313.84    438.57    1.002
r(A<->C){all}   0.185624    0.000242    0.155455    0.215792    0.185454    758.46    782.07    1.000
r(A<->G){all}   0.300678    0.000404    0.260727    0.337922    0.300057    774.12    795.29    1.001
r(A<->T){all}   0.078302    0.000143    0.054212    0.100805    0.078103    971.24    977.03    1.000
r(C<->G){all}   0.051158    0.000138    0.028934    0.074668    0.050693    562.20    867.17    1.000
r(C<->T){all}   0.309103    0.000425    0.269554    0.349853    0.309032    793.72    856.49    1.000
r(G<->T){all}   0.075134    0.000143    0.051649    0.098301    0.074871    862.83    930.02    1.002
pi(A){all}      0.294358    0.000072    0.278452    0.311244    0.294462   1138.11   1141.69    1.000
pi(C){all}      0.261394    0.000072    0.244542    0.277701    0.261179   1085.69   1103.73    1.000
pi(G){all}      0.215886    0.000064    0.200295    0.230816    0.215902    978.88    979.27    1.000
pi(T){all}      0.228363    0.000068    0.211503    0.243501    0.228359    901.98    996.74    1.000
alpha{1,2}      0.595336    0.002597    0.496835    0.695486    0.593339    892.48   1080.54    1.002
alpha{3}        4.363232    0.968347    2.639656    6.280398    4.235002   1347.73   1424.37    1.000
pinvar{all}     0.008978    0.000056    0.000001    0.023443    0.007056   1161.97   1286.00    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	-5177.938961
Model 2: PositiveSelection	-5140.266329
Model 0: one-ratio	-5251.286164
Model 3: discrete	-5127.932851
Model 7: beta	-5197.504761
Model 8: beta&w>1	-5143.269023


Model 0 vs 1	146.69440600000053

Model 2 vs 1	75.34526399999959

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

   274 T      1.000**       29.368
   275 S      1.000**       29.368

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

   250 T      0.501         5.504 +- 4.531
   274 T      1.000**       10.090 +- 0.701
   275 S      1.000**       10.090 +- 0.701


Model 8 vs 7	108.47147600000062

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

   274 T      1.000**       24.319
   275 S      1.000**       24.319

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

   250 T      0.645         6.634 +- 4.503
   274 T      1.000**       10.024 +- 0.754
   275 S      1.000**       10.024 +- 0.754