--- EXPERIMENT NOTES




 --- EXPERIMENT PROPERTIES

#Fri Nov 25 14:53:15 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-PI/input.fasta
input.names=
mrbayes.params=
codeml.params=



 --- PSRF SUMMARY

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

Run   Arithmetic mean   Harmonic mean
--------------------------------------
1      -1544.03         -1566.45
2      -1543.90         -1564.51
--------------------------------------
TOTAL    -1543.96         -1565.89
--------------------------------------


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

95% HPD Interval
--------------------
Parameter         Mean      Variance     Lower       Upper       Median    min ESS*  avg ESS    PSRF+
------------------------------------------------------------------------------------------------------
TL{all}         0.247045    0.001636    0.177596    0.328592    0.243450   1189.90   1293.89    1.000
r(A<->C){all}   0.110983    0.001157    0.048982    0.178579    0.108028    787.16    842.95    1.000
r(A<->G){all}   0.152915    0.001815    0.078436    0.238473    0.148799    646.84    730.91    1.005
r(A<->T){all}   0.066747    0.001069    0.011132    0.130994    0.062106    629.97    674.62    1.002
r(C<->G){all}   0.063010    0.000675    0.018255    0.115389    0.059807    878.35    972.98    1.001
r(C<->T){all}   0.556295    0.005080    0.414837    0.686740    0.557223    677.70    679.63    1.002
r(G<->T){all}   0.050050    0.000802    0.005088    0.105033    0.045172    833.42    888.69    1.000
pi(A){all}      0.286030    0.000267    0.252536    0.315985    0.285748   1309.39   1318.38    1.000
pi(C){all}      0.261023    0.000233    0.231396    0.291531    0.260978   1318.68   1338.60    1.000
pi(G){all}      0.258045    0.000244    0.227258    0.288747    0.257648   1379.09   1379.46    1.000
pi(T){all}      0.194902    0.000195    0.166298    0.220556    0.194473   1086.63   1216.81    1.000
alpha{1,2}      0.057764    0.001807    0.000154    0.136396    0.049779   1084.70   1261.54    1.001
alpha{3}        2.078999    0.677484    0.786439    3.739639    1.936604   1265.92   1342.37    1.000
pinvar{all}     0.475833    0.008547    0.287817    0.641833    0.487741   1115.95   1225.67    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	-1451.36118
Model 2: PositiveSelection	-1451.36118
Model 0: one-ratio	-1458.92382
Model 3: discrete	-1451.332921
Model 7: beta	-1451.333746
Model 8: beta&w>1	-1451.361179


Model 0 vs 1	15.125279999999748

Model 2 vs 1	0.0

Model 8 vs 7	0.054865999999947235