--- 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
