--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Jul 14 02:32:04 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_N3/NS4B_4/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_4/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_N3/NS4B_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6409.09         -6458.67
2      -6410.03         -6451.32
--------------------------------------
TOTAL    -6409.45         -6457.98
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_4/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_N3/NS4B_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         7.909196    0.270976    6.959896    8.964944    7.888652    675.83    829.13    1.000
r(A<->C){all}   0.036271    0.000042    0.024257    0.049454    0.035922    766.98    906.55    1.000
r(A<->G){all}   0.194807    0.000304    0.161512    0.230717    0.194421    671.71    682.69    1.000
r(A<->T){all}   0.050833    0.000055    0.037212    0.065883    0.050450    678.28    710.60    1.000
r(C<->G){all}   0.019573    0.000043    0.007049    0.032079    0.018900    841.11    926.17    1.000
r(C<->T){all}   0.663741    0.000480    0.622244    0.707063    0.663914    553.08    650.94    1.000
r(G<->T){all}   0.034776    0.000064    0.019976    0.050886    0.034309    709.74    754.67    1.000
pi(A){all}      0.334330    0.000157    0.311186    0.359637    0.334279    773.28    813.87    1.000
pi(C){all}      0.238828    0.000117    0.219027    0.261326    0.238623    744.87    834.79    1.000
pi(G){all}      0.215352    0.000116    0.193782    0.236033    0.215248    877.48    879.94    1.000
pi(T){all}      0.211491    0.000093    0.193446    0.230742    0.211482    584.31    729.94    1.000
alpha{1,2}      0.183191    0.000130    0.162631    0.206899    0.182649   1170.96   1235.41    1.000
alpha{3}        4.157995    0.585639    2.799276    5.754164    4.085948   1380.22   1385.46    1.001
pinvar{all}     0.131907    0.000848    0.076748    0.190035    0.131558    995.81   1104.42    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	-5898.529147
Model 2: PositiveSelection	-5898.529147
Model 0: one-ratio	-5942.816926
Model 3: discrete	-5838.7087
Model 7: beta	-5842.545025
Model 8: beta&w>1	-5840.12694


Model 0 vs 1	88.57555800000046

Model 2 vs 1	0.0

Model 8 vs 7	4.836170000000493