--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 16 22:17:13 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_2_2/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_2_2/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_2_2/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1     -16474.34        -16517.23
2     -16470.66        -16524.86
--------------------------------------
TOTAL   -16471.33        -16524.17
--------------------------------------


Model parameter summaries over the runs sampled in files
"/data/repeat/ns3_2_2/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/repeat/ns3_2_2/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_2_2/Muscle/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         9.099681    0.194060    8.323410   10.026560    9.075611    383.12    561.46    1.001
r(A<->C){all}   0.034636    0.000014    0.026914    0.041310    0.034574    687.82    724.85    1.000
r(A<->G){all}   0.205783    0.000123    0.183685    0.227445    0.205538    317.35    400.45    1.000
r(A<->T){all}   0.040326    0.000016    0.032367    0.048120    0.040322    783.33    865.44    1.001
r(C<->G){all}   0.015969    0.000012    0.009208    0.022746    0.015861    780.91    830.58    1.000
r(C<->T){all}   0.681059    0.000183    0.654150    0.706759    0.681408    307.00    381.33    1.000
r(G<->T){all}   0.022228    0.000017    0.014546    0.030739    0.022118    616.67    653.64    1.000
pi(A){all}      0.360611    0.000060    0.345979    0.375990    0.360551    799.09    825.63    1.001
pi(C){all}      0.212207    0.000040    0.200288    0.224631    0.212081    615.22    706.87    1.000
pi(G){all}      0.227403    0.000044    0.213735    0.239334    0.227378    546.86    606.56    1.000
pi(T){all}      0.199779    0.000036    0.188522    0.211559    0.199575    763.11    850.04    1.001
alpha{1,2}      0.156759    0.000041    0.144420    0.168852    0.156553   1178.05   1282.77    1.001
alpha{3}        6.347302    0.905175    4.699067    8.225644    6.297386   1314.88   1407.94    1.000
pinvar{all}     0.119365    0.000283    0.088198    0.152563    0.119169   1329.32   1343.77    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	-15870.135482
Model 2: PositiveSelection	-15870.135482
Model 0: one-ratio	-15944.128229
Model 3: discrete	-15702.282049
Model 7: beta	-15706.727427
Model 8: beta&w>1	-15706.19979


Model 0 vs 1	147.98549400000047

Model 2 vs 1	0.0

Model 8 vs 7	1.0552739999984624