--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat May 26 02:47:28 WEST 2018
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/DNG_A1/NS1_2/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A1/NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS1_2/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/DNG_A1/NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -9265.11         -9307.68
2      -9266.12         -9305.59
--------------------------------------
TOTAL    -9265.49         -9307.11
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A1/NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS1_2/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/DNG_A1/NS1_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         7.970151    0.237967    7.019284    8.910147    7.950069    836.22    919.31    1.000
r(A<->C){all}   0.028854    0.000023    0.019698    0.038464    0.028727    860.12    961.97    1.000
r(A<->G){all}   0.245284    0.000300    0.212765    0.279057    0.244863    521.38    523.02    1.004
r(A<->T){all}   0.053745    0.000043    0.041244    0.066283    0.053517    687.98    730.23    1.001
r(C<->G){all}   0.024734    0.000035    0.013521    0.036114    0.024344    796.90    827.17    1.000
r(C<->T){all}   0.624602    0.000421    0.583005    0.662000    0.624501    479.35    491.79    1.005
r(G<->T){all}   0.022782    0.000041    0.010718    0.035672    0.022400    670.79    748.34    1.000
pi(A){all}      0.353789    0.000110    0.332998    0.373788    0.353559    780.98    812.23    1.003
pi(C){all}      0.231192    0.000077    0.213862    0.248331    0.231200    561.47    735.84    1.001
pi(G){all}      0.219098    0.000078    0.202218    0.236702    0.219123    486.90    509.10    1.000
pi(T){all}      0.195920    0.000063    0.181301    0.211649    0.195798    624.57    661.46    1.003
alpha{1,2}      0.194928    0.000149    0.172175    0.219697    0.193979   1257.51   1295.19    1.000
alpha{3}        4.445273    0.607220    3.090996    5.975314    4.362642   1432.62   1438.00    1.002
pinvar{all}     0.132247    0.000503    0.089100    0.175918    0.132460   1160.43   1251.31    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	-8913.519685
Model 2: PositiveSelection	-8913.519685
Model 0: one-ratio	-9056.978282
Model 3: discrete	-8808.369922
Model 7: beta	-8818.46621
Model 8: beta&w>1	-8807.758727


Model 0 vs 1	286.9171940000015

Model 2 vs 1	0.0

Model 8 vs 7	21.414966000000277

Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
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:KY586424|Organism:Dengue_virus|Strain_Name:Ser1_Thailand_BangkokSeq_99|Protein_Name:nonstructural_protein_1|Gene_Symbol:NS1)

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

    98 G      0.790         1.328 +- 0.346
   128 V      0.775         1.316 +- 0.351
   131 S      0.541         1.098 +- 0.452
   178 V      0.834         1.364 +- 0.320
   224 I      0.510         1.066 +- 0.459