--- 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
