--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 25 13:57:54 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-PE/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -1342.72         -1382.31
2      -1342.33         -1381.64
--------------------------------------
TOTAL    -1342.51         -1382.03
--------------------------------------


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

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.473544    0.067333    0.142869    1.018249    0.400158    662.16    821.53    1.001
r(A<->C){all}   0.068818    0.001499    0.007393    0.146321    0.062591    823.08    826.55    1.000
r(A<->G){all}   0.221598    0.013474    0.036367    0.454872    0.201844    188.17    190.86    1.007
r(A<->T){all}   0.068243    0.001607    0.005154    0.148570    0.060632    497.57    514.43    1.000
r(C<->G){all}   0.045412    0.000869    0.000300    0.102767    0.039104    359.43    459.65    1.002
r(C<->T){all}   0.578885    0.020094    0.316472    0.850431    0.581910    188.85    192.58    1.005
r(G<->T){all}   0.017044    0.000298    0.000001    0.051334    0.011402    575.97    635.25    1.000
pi(A){all}      0.279823    0.000253    0.248380    0.309435    0.279650    988.65   1223.69    1.000
pi(C){all}      0.259029    0.000238    0.228630    0.288443    0.258887    926.24    939.33    1.001
pi(G){all}      0.260970    0.000249    0.229218    0.291322    0.260985    911.35   1014.28    1.000
pi(T){all}      0.200178    0.000213    0.171262    0.227612    0.199568   1055.21   1121.96    1.000
alpha{1,2}      0.093441    0.000880    0.036617    0.165185    0.091221    822.79    970.66    1.000
alpha{3}        1.221985    0.460075    0.221013    2.559570    1.071760    826.19    995.06    1.000
pinvar{all}     0.824411    0.001262    0.756296    0.887993    0.828988    935.01   1086.18    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