--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed May 09 19:49:47 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/NS2A_5/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_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_N2/NS2A_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6687.90         -6749.29
2      -6689.43         -6740.72
--------------------------------------
TOTAL    -6688.40         -6748.60
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_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_N2/NS2A_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}        10.091904    0.507607    8.690828   11.466010   10.061140    553.20    640.55    1.000
r(A<->C){all}   0.047588    0.000074    0.032047    0.065131    0.047219    702.10    799.36    1.000
r(A<->G){all}   0.221296    0.000317    0.187808    0.256169    0.220797    569.56    596.25    1.002
r(A<->T){all}   0.050872    0.000067    0.035392    0.067844    0.050537    806.83    835.57    1.000
r(C<->G){all}   0.030681    0.000080    0.014980    0.049214    0.030119    803.43    883.96    1.000
r(C<->T){all}   0.613832    0.000478    0.569521    0.653827    0.613844    607.62    656.62    1.000
r(G<->T){all}   0.035731    0.000076    0.017969    0.051533    0.035228    701.94    703.63    1.001
pi(A){all}      0.306469    0.000125    0.284766    0.328552    0.306235    805.97    816.20    1.001
pi(C){all}      0.215753    0.000092    0.197790    0.235027    0.215828    879.00    908.98    1.000
pi(G){all}      0.242005    0.000106    0.220428    0.261123    0.241868    876.44    940.60    1.000
pi(T){all}      0.235773    0.000099    0.215658    0.254474    0.235757    613.95    768.23    1.002
alpha{1,2}      0.390371    0.001521    0.321652    0.469621    0.387710   1119.36   1172.20    1.000
alpha{3}        3.635619    0.662038    2.245630    5.334005    3.535999   1171.84   1336.42    1.000
pinvar{all}     0.029416    0.000367    0.000015    0.064571    0.026258   1135.68   1145.80    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	-6348.524594
Model 2: PositiveSelection	-6348.524594
Model 0: one-ratio	-6369.868452
Model 3: discrete	-6295.535119
Model 7: beta	-6298.611008
Model 8: beta&w>1	-6296.870221


Model 0 vs 1	42.687715999998545

Model 2 vs 1	0.0

Model 8 vs 7	3.481573999999455