--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Mon Jul 16 01:58:44 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/prM_5/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/prM_5/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/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -3991.97 -4039.96
2 -3993.39 -4036.76
--------------------------------------
TOTAL -3992.45 -4039.30
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/prM_5/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/prM_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 6.987316 0.293178 5.996340 8.133070 6.986983 786.02 825.63 1.000
r(A<->C){all} 0.034580 0.000082 0.017162 0.051414 0.034013 749.78 750.81 1.000
r(A<->G){all} 0.197104 0.000526 0.156115 0.244059 0.196366 491.64 522.21 1.000
r(A<->T){all} 0.071971 0.000163 0.047081 0.096817 0.071476 755.07 804.63 1.000
r(C<->G){all} 0.019637 0.000053 0.006410 0.033985 0.019142 564.59 658.58 1.003
r(C<->T){all} 0.641973 0.000819 0.587056 0.699631 0.641654 436.67 486.98 1.000
r(G<->T){all} 0.034735 0.000105 0.016579 0.057009 0.034069 527.52 553.41 1.000
pi(A){all} 0.296550 0.000213 0.267389 0.324539 0.296269 714.66 788.27 1.000
pi(C){all} 0.252154 0.000176 0.225158 0.276075 0.252478 571.56 703.95 1.000
pi(G){all} 0.249473 0.000206 0.219261 0.274879 0.249578 776.93 823.09 1.001
pi(T){all} 0.201824 0.000137 0.177387 0.222604 0.201756 685.32 696.12 1.003
alpha{1,2} 0.187433 0.000231 0.158756 0.217464 0.186088 1273.63 1285.00 1.000
alpha{3} 3.302929 0.490587 2.062023 4.679707 3.216638 1398.69 1435.74 1.001
pinvar{all} 0.045740 0.000794 0.000274 0.097667 0.041844 1106.30 1218.31 1.001
------------------------------------------------------------------------------------------------------
* 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 -3815.847278
Model 2: PositiveSelection -3815.847278
Model 0: one-ratio -3821.791197
Model 3: discrete -3778.722686
Model 7: beta -3779.14827
Model 8: beta&w>1 -3779.14993
Model 0 vs 1 11.887837999999647
Model 2 vs 1 0.0
Model 8 vs 7 0.003319999999803258
