--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu Jul 12 02:13:48 WEST 2018
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=MUSCLE
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/ADOPS1/DNG_N3/NS4B_1/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_1/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/ADOPS1/DNG_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -5962.81 -6007.61
2 -5961.47 -6005.50
--------------------------------------
TOTAL -5961.93 -6007.03
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_1/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/ADOPS1/DNG_N3/NS4B_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 7.289096 0.234855 6.392444 8.228090 7.277219 887.52 908.19 1.000
r(A<->C){all} 0.044034 0.000059 0.029100 0.059385 0.043968 923.45 991.33 1.000
r(A<->G){all} 0.231089 0.000413 0.193975 0.272343 0.230222 523.92 537.84 1.001
r(A<->T){all} 0.057129 0.000080 0.040361 0.074667 0.056645 843.52 888.62 1.004
r(C<->G){all} 0.028866 0.000066 0.013203 0.044447 0.028441 673.83 773.88 1.000
r(C<->T){all} 0.614799 0.000607 0.567814 0.662558 0.615368 516.69 525.79 1.003
r(G<->T){all} 0.024084 0.000062 0.009297 0.039176 0.023592 785.81 806.63 1.001
pi(A){all} 0.337796 0.000148 0.315387 0.362197 0.337679 943.87 985.45 1.001
pi(C){all} 0.232480 0.000107 0.212495 0.252871 0.232382 802.77 911.41 1.001
pi(G){all} 0.217346 0.000113 0.195555 0.237754 0.217197 800.54 888.79 1.000
pi(T){all} 0.212378 0.000093 0.192874 0.230510 0.212287 835.04 898.33 1.001
alpha{1,2} 0.179789 0.000165 0.155748 0.204818 0.179078 902.08 1042.60 1.000
alpha{3} 4.313709 0.748055 2.719269 5.994901 4.203316 1416.71 1458.85 1.001
pinvar{all} 0.131891 0.000769 0.080795 0.186981 0.131564 1235.35 1243.18 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 -5408.319805
Model 2: PositiveSelection -5408.319805
Model 0: one-ratio -5421.441971
Model 3: discrete -5346.019052
Model 7: beta -5347.505404
Model 8: beta&w>1 -5347.507834
Model 0 vs 1 26.244332000000213
Model 2 vs 1 0.0
Model 8 vs 7 0.004859999999098363
