--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Tue May 08 20:43:33 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_3/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_3/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_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -6776.12         -6822.39
2      -6776.10         -6822.98
--------------------------------------
TOTAL    -6776.11         -6822.73
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_3/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_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         9.828963    0.467969    8.512125   11.133490    9.798801    667.69    801.59    1.000
r(A<->C){all}   0.050639    0.000077    0.033863    0.067419    0.050255    629.65    698.70    1.000
r(A<->G){all}   0.211261    0.000297    0.177621    0.245863    0.211006    484.50    506.60    1.000
r(A<->T){all}   0.041871    0.000057    0.026911    0.056196    0.041580    944.45    974.39    1.000
r(C<->G){all}   0.032888    0.000075    0.016924    0.050481    0.032391    599.14    730.39    1.000
r(C<->T){all}   0.623248    0.000460    0.581696    0.665770    0.623842    474.14    474.84    1.000
r(G<->T){all}   0.040094    0.000072    0.024114    0.057696    0.039700    758.39    788.28    1.001
pi(A){all}      0.303776    0.000130    0.279916    0.325157    0.303750    737.25    855.44    1.000
pi(C){all}      0.211762    0.000083    0.193898    0.228724    0.211611    777.38    810.89    1.000
pi(G){all}      0.248193    0.000106    0.227528    0.268238    0.247983    747.70    834.34    1.000
pi(T){all}      0.236269    0.000103    0.215188    0.254720    0.236186    634.33    762.86    1.002
alpha{1,2}      0.392847    0.001535    0.322209    0.472548    0.389588   1220.04   1307.98    1.000
alpha{3}        4.436929    0.948605    2.636499    6.329792    4.332465   1280.10   1341.75    1.000
pinvar{all}     0.025704    0.000336    0.000003    0.060718    0.022583   1234.58   1236.36    1.001
------------------------------------------------------------------------------------------------------
* 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	-6501.350616
Model 2: PositiveSelection	-6501.350616
Model 0: one-ratio	-6515.426241
Model 3: discrete	-6441.768847
Model 7: beta	-6442.844059
Model 8: beta&w>1	-6442.846211


Model 0 vs 1	28.1512500000008

Model 2 vs 1	0.0

Model 8 vs 7	0.004304000000047381