--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Nov 12 04:38:38 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/200/CG9485-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/200/CG9485-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/200/CG9485-PC/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/200/CG9485-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -18464.21 -18483.73
2 -18464.80 -18478.54
--------------------------------------
TOTAL -18464.46 -18483.04
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/200/CG9485-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/200/CG9485-PC/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/200/CG9485-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.439974 0.002345 1.344708 1.532492 1.439998 1114.81 1221.84 1.000
r(A<->C){all} 0.096319 0.000055 0.081899 0.110355 0.096170 1056.40 1125.30 1.000
r(A<->G){all} 0.278861 0.000174 0.252324 0.303120 0.279054 820.99 887.66 1.000
r(A<->T){all} 0.119364 0.000108 0.099993 0.140327 0.119168 951.13 1010.84 1.000
r(C<->G){all} 0.044720 0.000019 0.035649 0.052945 0.044655 976.40 1057.48 1.000
r(C<->T){all} 0.383394 0.000213 0.354973 0.412469 0.383476 805.79 943.45 1.000
r(G<->T){all} 0.077343 0.000047 0.064709 0.091147 0.077116 995.29 1000.08 1.000
pi(A){all} 0.217330 0.000031 0.206576 0.228133 0.217411 860.41 933.59 1.000
pi(C){all} 0.290305 0.000035 0.278023 0.301203 0.290284 1038.25 1112.38 1.000
pi(G){all} 0.277010 0.000037 0.264839 0.288358 0.277079 1076.51 1093.98 1.001
pi(T){all} 0.215356 0.000028 0.204624 0.225619 0.215334 887.02 1023.10 1.000
alpha{1,2} 0.128926 0.000032 0.118160 0.139930 0.128887 1288.96 1306.90 1.000
alpha{3} 6.315121 1.231391 4.425888 8.590092 6.214561 1248.54 1338.93 1.000
pinvar{all} 0.315301 0.000302 0.282735 0.349774 0.315410 1126.96 1241.37 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 -17342.254258
Model 2: PositiveSelection -17342.254258
Model 0: one-ratio -17479.385831
Model 3: discrete -17274.531656
Model 7: beta -17276.251085
Model 8: beta&w>1 -17275.432899
Model 0 vs 1 274.2631459999975
Model 2 vs 1 0.0
Model 8 vs 7 1.636372000000847
