--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 25 15:04:20 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
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/ADOPS/1/14-3-3zeta-PJ/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

      Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PJ/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/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -1342.81         -1383.83
2      -1341.12         -1382.53
--------------------------------------
TOTAL    -1341.65         -1383.38
--------------------------------------


Model parameter summaries over the runs sampled in files
"/opt/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/1/14-3-3zeta-PJ/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/ADOPS/1/14-3-3zeta-PJ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.476780    0.063051    0.152655    1.002599    0.408395    720.93    859.17    1.000
r(A<->C){all}   0.070402    0.001539    0.005375    0.145904    0.063982    441.79    479.66    1.000
r(A<->G){all}   0.236200    0.015525    0.037854    0.485439    0.211056    134.28    197.18    1.000
r(A<->T){all}   0.065136    0.001435    0.006683    0.142577    0.058541    428.13    482.49    1.004
r(C<->G){all}   0.045393    0.000819    0.002140    0.100972    0.039549    616.43    616.72    1.000
r(C<->T){all}   0.565716    0.020514    0.303397    0.848663    0.571163    162.65    183.51    1.000
r(G<->T){all}   0.017153    0.000301    0.000014    0.051937    0.011922    558.49    699.48    1.000
pi(A){all}      0.279983    0.000249    0.249437    0.310811    0.279229    992.66   1047.16    1.000
pi(C){all}      0.259685    0.000257    0.228701    0.290107    0.259279   1075.92   1150.07    1.000
pi(G){all}      0.259899    0.000250    0.229396    0.290424    0.259771   1074.32   1149.41    1.001
pi(T){all}      0.200434    0.000203    0.170247    0.226428    0.200408    880.29   1089.11    1.000
alpha{1,2}      0.094111    0.000797    0.036327    0.156475    0.091984    906.89   1098.06    1.000
alpha{3}        1.193212    0.384872    0.249971    2.419900    1.052090    867.19    955.70    1.000
pinvar{all}     0.826546    0.001175    0.758937    0.885881    0.830428    813.30    903.53    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	-1263.066771
Model 2: PositiveSelection	-1263.066771
Model 0: one-ratio	-1264.026193
Model 3: discrete	-1263.063085
Model 7: beta	-1263.3924
Model 8: beta&w>1	-1263.066768


Model 0 vs 1	1.9188439999998081

Model 2 vs 1	0.0

Model 8 vs 7	0.6512640000000829