--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Wed May 09 12:45:09 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_4/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_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_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6452.27         -6498.03
2      -6452.42         -6496.20
--------------------------------------
TOTAL    -6452.34         -6497.49
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_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_N2/NS2A_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}         9.336506    0.452743    8.038047   10.687740    9.301376    464.62    602.83    1.000
r(A<->C){all}   0.047047    0.000085    0.029947    0.065949    0.046691    679.13    740.11    1.000
r(A<->G){all}   0.214645    0.000326    0.178394    0.247501    0.214197    503.95    553.81    1.002
r(A<->T){all}   0.057231    0.000076    0.041865    0.075537    0.056888    791.97    899.13    1.000
r(C<->G){all}   0.051669    0.000109    0.031085    0.070905    0.051188    654.72    739.61    1.000
r(C<->T){all}   0.603610    0.000499    0.562566    0.647572    0.602958    369.49    481.63    1.002
r(G<->T){all}   0.025798    0.000068    0.009991    0.041353    0.025378    753.67    796.04    1.000
pi(A){all}      0.306025    0.000126    0.284311    0.327768    0.305865    594.29    684.45    1.000
pi(C){all}      0.215488    0.000092    0.197316    0.234215    0.215474    719.79    744.39    1.000
pi(G){all}      0.241226    0.000110    0.220255    0.260976    0.241085    860.57    921.65    1.000
pi(T){all}      0.237261    0.000098    0.217759    0.256455    0.236936    771.12    852.37    1.000
alpha{1,2}      0.390034    0.001514    0.320042    0.466318    0.387319    712.54    958.34    1.000
alpha{3}        4.174785    0.951195    2.517902    6.140725    4.048279   1040.30   1142.35    1.000
pinvar{all}     0.026314    0.000314    0.000006    0.060721    0.023523   1233.55   1312.99    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	-6133.329351
Model 2: PositiveSelection	-6133.329351
Model 0: one-ratio	-6149.747654
Model 3: discrete	-6082.695715
Model 7: beta	-6083.05543
Model 8: beta&w>1	-6083.055832


Model 0 vs 1	32.83660599999894

Model 2 vs 1	0.0

Model 8 vs 7	8.039999993343372E-4