--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed Jul 11 13:57:42 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/NS4A_4/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4A_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/NS4A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -3753.17         -3800.41
2      -3754.04         -3800.99
--------------------------------------
TOTAL    -3753.51         -3800.74
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4A_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/NS4A_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}         8.098356    0.367562    6.990136    9.331580    8.075128    849.70    881.81    1.000
r(A<->C){all}   0.043895    0.000105    0.025136    0.065025    0.043320    664.81    696.84    1.000
r(A<->G){all}   0.190223    0.000495    0.146946    0.233164    0.189738    385.74    428.16    1.000
r(A<->T){all}   0.064686    0.000155    0.040939    0.088692    0.064207    446.22    583.73    1.000
r(C<->G){all}   0.027301    0.000071    0.012491    0.045087    0.026844    692.54    853.46    1.000
r(C<->T){all}   0.635383    0.000852    0.576898    0.690485    0.635869    366.89    437.28    1.000
r(G<->T){all}   0.038512    0.000110    0.019814    0.059380    0.037523    627.88    731.84    1.001
pi(A){all}      0.305665    0.000247    0.273543    0.334703    0.305380    680.27    838.68    1.000
pi(C){all}      0.250639    0.000210    0.221753    0.277477    0.250484    533.26    630.29    1.000
pi(G){all}      0.234653    0.000217    0.207266    0.264792    0.234283    605.93    643.69    1.001
pi(T){all}      0.209043    0.000171    0.182966    0.234211    0.208450    650.15    677.63    1.000
alpha{1,2}      0.267367    0.000706    0.217213    0.320410    0.265240   1501.00   1501.00    1.000
alpha{3}        4.819807    1.116250    2.919535    6.892745    4.688781   1258.12   1379.56    1.000
pinvar{all}     0.026559    0.000421    0.000005    0.068794    0.021992   1223.81   1362.41    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	-3525.68507
Model 2: PositiveSelection	-3525.684975
Model 0: one-ratio	-3525.684975
Model 3: discrete	-3506.354755
Model 7: beta	-3507.118971
Model 8: beta&w>1	-3507.120231


Model 0 vs 1	1.899999997476698E-4

Model 2 vs 1	1.899999997476698E-4

Model 8 vs 7	0.0025200000000040745