--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sun May 13 01:28:00 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_N2/NS3_1/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS3_1/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_N2/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -14034.54        -14081.15
2     -14034.65        -14078.23
--------------------------------------
TOTAL   -14034.59        -14080.51
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS3_1/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_N2/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         7.996487    0.185794    7.149314    8.846762    7.988390    543.38    644.09    1.001
r(A<->C){all}   0.038383    0.000021    0.029729    0.047227    0.038353    721.52    800.96    1.000
r(A<->G){all}   0.188100    0.000142    0.165009    0.211106    0.187959    356.37    419.35    1.000
r(A<->T){all}   0.040573    0.000023    0.031738    0.050365    0.040334    797.30    824.24    1.002
r(C<->G){all}   0.016096    0.000014    0.008840    0.023246    0.015875    727.53    780.20    1.002
r(C<->T){all}   0.692003    0.000223    0.661887    0.718734    0.692027    322.81    410.10    1.001
r(G<->T){all}   0.024844    0.000022    0.015476    0.033641    0.024562    825.30    840.93    1.000
pi(A){all}      0.357829    0.000064    0.342153    0.373484    0.357717    725.17    755.45    1.000
pi(C){all}      0.216198    0.000043    0.204034    0.229648    0.216178    692.29    705.08    1.000
pi(G){all}      0.231022    0.000050    0.218207    0.245644    0.230743    677.20    695.85    1.001
pi(T){all}      0.194951    0.000037    0.182680    0.206027    0.194944    669.47    715.30    1.000
alpha{1,2}      0.157489    0.000045    0.144040    0.170021    0.157265   1175.26   1249.58    1.000
alpha{3}        5.665703    0.830564    4.096319    7.577616    5.564216   1224.90   1282.90    1.001
pinvar{all}     0.124441    0.000298    0.091971    0.159184    0.124127   1179.28   1302.67    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	-13230.463408
Model 2: PositiveSelection	-13230.463408
Model 0: one-ratio	-13264.227654
Model 3: discrete	-13096.500061
Model 7: beta	-13083.261299
Model 8: beta&w>1	-13082.522104


Model 0 vs 1	67.52849200000128

Model 2 vs 1	0.0

Model 8 vs 7	1.4783900000002177