--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat May 05 18:19:45 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_N1/NS1_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/NS1_3/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_N1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -8659.23         -8701.67
2      -8655.30         -8708.49
--------------------------------------
TOTAL    -8655.98         -8707.79
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N1/NS1_3/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_N1/NS1_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         7.217333    0.196450    6.341859    8.071543    7.200145    618.81    622.71    1.000
r(A<->C){all}   0.034323    0.000029    0.024379    0.045093    0.034057    890.21    948.28    1.000
r(A<->G){all}   0.208871    0.000253    0.177440    0.238838    0.208254    566.79    577.37    1.000
r(A<->T){all}   0.050874    0.000044    0.038052    0.064030    0.050715    943.50    965.61    1.000
r(C<->G){all}   0.029970    0.000043    0.017690    0.042647    0.029464    802.83    877.05    1.000
r(C<->T){all}   0.652539    0.000388    0.612843    0.689476    0.652902    599.27    652.44    1.000
r(G<->T){all}   0.023423    0.000050    0.009930    0.037240    0.023040    829.69    829.96    1.000
pi(A){all}      0.345922    0.000108    0.325470    0.366320    0.345531    798.16    841.71    1.001
pi(C){all}      0.228843    0.000075    0.212410    0.246066    0.228635    879.90    902.70    1.000
pi(G){all}      0.227934    0.000086    0.209420    0.245739    0.227872    787.64    839.53    1.000
pi(T){all}      0.197301    0.000062    0.181947    0.212601    0.197288    823.47    840.55    1.001
alpha{1,2}      0.201507    0.000179    0.175757    0.226154    0.200465   1072.30   1236.19    1.001
alpha{3}        6.006094    1.250435    3.997584    8.220455    5.909205   1291.27   1392.20    1.000
pinvar{all}     0.121053    0.000483    0.078434    0.162645    0.120570   1326.87   1342.95    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	-7919.185132
Model 2: PositiveSelection	-7919.185132
Model 0: one-ratio	-8024.578286
Model 3: discrete	-7839.173789
Model 7: beta	-7847.991435
Model 8: beta&w>1	-7844.357375


Model 0 vs 1	210.78630800000064

Model 2 vs 1	0.0

Model 8 vs 7	7.268120000000636

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:JN851128|Organism:Dengue_virus_2|Strain_Name:SGEHI(D2)0232Y06|Protein_Name:Nonstructural_protein_NS1|Gene_Symbol:NS1)

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

    97 Q      0.738         1.296 +- 0.395
   126 L      0.601         1.159 +- 0.442