--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Sat Jul 14 17:58:13 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_5/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_5/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_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -5689.01         -5737.23
2      -5690.32         -5740.51
--------------------------------------
TOTAL    -5689.46         -5739.85
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_5/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_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         6.832959    0.233609    5.931382    7.798695    6.823122    570.30    736.69    1.002
r(A<->C){all}   0.040638    0.000058    0.026585    0.056070    0.040369    891.07    969.76    1.000
r(A<->G){all}   0.188175    0.000323    0.153356    0.224146    0.187574    727.84    737.74    1.001
r(A<->T){all}   0.046890    0.000070    0.030528    0.063644    0.046546    805.41    845.57    1.000
r(C<->G){all}   0.037397    0.000080    0.020284    0.054620    0.037162    779.82    794.00    1.000
r(C<->T){all}   0.668077    0.000527    0.622085    0.711732    0.668232    670.73    683.24    1.002
r(G<->T){all}   0.018823    0.000047    0.006274    0.032361    0.018129    692.83    800.76    1.000
pi(A){all}      0.333964    0.000153    0.309510    0.356708    0.334089    981.75    984.73    1.000
pi(C){all}      0.233548    0.000104    0.214836    0.253613    0.233208    984.44    989.05    1.000
pi(G){all}      0.216720    0.000123    0.194423    0.236870    0.216726    883.67    908.64    1.000
pi(T){all}      0.215767    0.000102    0.196737    0.236394    0.215845    950.88    954.41    1.000
alpha{1,2}      0.181292    0.000184    0.156042    0.208022    0.180678   1347.44   1424.22    1.000
alpha{3}        4.918173    1.001275    3.107344    6.857062    4.828633   1355.50   1400.59    1.000
pinvar{all}     0.131331    0.000907    0.071104    0.187147    0.131162   1050.07   1175.54    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	-5107.099971
Model 2: PositiveSelection	-5107.099971
Model 0: one-ratio	-5141.931236
Model 3: discrete	-5040.227209
Model 7: beta	-5042.357472
Model 8: beta&w>1	-5042.359827


Model 0 vs 1	69.66253000000142

Model 2 vs 1	0.0

Model 8 vs 7	0.004710000001068693