--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Tue Nov 13 23:59:33 GMT 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=/usr/bin/
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb
tcoffee.bin=t_coffee
mrbayes.dir=/opt/mrbayes_3.2.2/src
tcoffee.dir=
tcoffee.minScore=3
input.fasta=
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/data/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p":
(Use the harmonic mean for Bayes factor comparisons of models)

(Values are saved to the file /data/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -15023.98        -15061.84
2     -15025.14        -15063.44
--------------------------------------
TOTAL   -15024.40        -15062.93
--------------------------------------


Model parameter summaries over the runs sampled in files
"/data/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_4/Muscle/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 "/data/repeat/ns3_4/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         8.142768    0.178056    7.312768    8.917170    8.134761    508.04    750.36    1.000
r(A<->C){all}   0.036531    0.000017    0.028414    0.044292    0.036486    729.96    854.62    1.000
r(A<->G){all}   0.199935    0.000145    0.176875    0.224298    0.199886    378.33    429.99    1.003
r(A<->T){all}   0.040589    0.000020    0.031458    0.048652    0.040562    502.64    689.70    1.000
r(C<->G){all}   0.019217    0.000014    0.012086    0.026592    0.019035    856.59    906.08    1.000
r(C<->T){all}   0.684672    0.000215    0.656985    0.714113    0.684637    428.79    441.27    1.002
r(G<->T){all}   0.019055    0.000017    0.011421    0.027215    0.018816    614.70    687.90    1.000
pi(A){all}      0.356276    0.000066    0.339888    0.371882    0.356212    638.40    744.26    1.000
pi(C){all}      0.219145    0.000044    0.206394    0.232256    0.219122    517.30    542.83    1.000
pi(G){all}      0.228976    0.000049    0.215660    0.243032    0.228948    561.05    623.81    1.001
pi(T){all}      0.195603    0.000037    0.184025    0.208137    0.195576    558.82    663.26    1.001
alpha{1,2}      0.161910    0.000051    0.147876    0.175571    0.161671   1094.53   1252.79    1.000
alpha{3}        5.358050    0.676307    3.913713    7.067442    5.279592   1371.88   1436.44    1.000
pinvar{all}     0.115719    0.000300    0.082447    0.150216    0.115379   1082.58   1171.53    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	-14400.462733
Model 2: PositiveSelection	-14400.462734
Model 0: one-ratio	-14440.654751
Model 3: discrete	-14263.518451
Model 7: beta	-14266.551944
Model 8: beta&w>1	-14266.558115


Model 0 vs 1	80.38403599999947

Model 2 vs 1	2.0000006770715117E-6

Model 8 vs 7	0.01234199999817065