--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Jul 14 02:32:04 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_4/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_4/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_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6409.09 -6458.67
2 -6410.03 -6451.32
--------------------------------------
TOTAL -6409.45 -6457.98
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_4/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_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 7.909196 0.270976 6.959896 8.964944 7.888652 675.83 829.13 1.000
r(A<->C){all} 0.036271 0.000042 0.024257 0.049454 0.035922 766.98 906.55 1.000
r(A<->G){all} 0.194807 0.000304 0.161512 0.230717 0.194421 671.71 682.69 1.000
r(A<->T){all} 0.050833 0.000055 0.037212 0.065883 0.050450 678.28 710.60 1.000
r(C<->G){all} 0.019573 0.000043 0.007049 0.032079 0.018900 841.11 926.17 1.000
r(C<->T){all} 0.663741 0.000480 0.622244 0.707063 0.663914 553.08 650.94 1.000
r(G<->T){all} 0.034776 0.000064 0.019976 0.050886 0.034309 709.74 754.67 1.000
pi(A){all} 0.334330 0.000157 0.311186 0.359637 0.334279 773.28 813.87 1.000
pi(C){all} 0.238828 0.000117 0.219027 0.261326 0.238623 744.87 834.79 1.000
pi(G){all} 0.215352 0.000116 0.193782 0.236033 0.215248 877.48 879.94 1.000
pi(T){all} 0.211491 0.000093 0.193446 0.230742 0.211482 584.31 729.94 1.000
alpha{1,2} 0.183191 0.000130 0.162631 0.206899 0.182649 1170.96 1235.41 1.000
alpha{3} 4.157995 0.585639 2.799276 5.754164 4.085948 1380.22 1385.46 1.001
pinvar{all} 0.131907 0.000848 0.076748 0.190035 0.131558 995.81 1104.42 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 -5898.529147
Model 2: PositiveSelection -5898.529147
Model 0: one-ratio -5942.816926
Model 3: discrete -5838.7087
Model 7: beta -5842.545025
Model 8: beta&w>1 -5840.12694
Model 0 vs 1 88.57555800000046
Model 2 vs 1 0.0
Model 8 vs 7 4.836170000000493
