--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Tue May 08 03:17:50 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_N2/NS2A_1/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_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_N2/NS2A_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6539.54 -6590.94
2 -6540.57 -6590.81
--------------------------------------
TOTAL -6539.92 -6590.88
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS2A_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS2A_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_N2/NS2A_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} 10.035575 0.518817 8.519632 11.338680 10.015700 535.07 620.36 1.001
r(A<->C){all} 0.040833 0.000074 0.023523 0.056574 0.040550 663.78 813.38 1.000
r(A<->G){all} 0.222407 0.000353 0.184121 0.257106 0.222003 559.63 591.89 1.000
r(A<->T){all} 0.056985 0.000077 0.040693 0.074357 0.056421 905.46 958.11 1.000
r(C<->G){all} 0.036676 0.000092 0.019354 0.055617 0.036136 792.54 808.49 1.000
r(C<->T){all} 0.615734 0.000523 0.570136 0.658323 0.616059 601.48 607.36 1.000
r(G<->T){all} 0.027363 0.000073 0.011832 0.044335 0.026995 742.66 750.60 1.000
pi(A){all} 0.300406 0.000123 0.278941 0.322175 0.300265 654.48 710.79 1.000
pi(C){all} 0.215637 0.000096 0.196564 0.234305 0.215464 820.72 917.01 1.002
pi(G){all} 0.243427 0.000109 0.223914 0.264082 0.243305 908.31 961.31 1.000
pi(T){all} 0.240530 0.000102 0.220850 0.261094 0.240318 766.31 794.89 1.000
alpha{1,2} 0.386116 0.001441 0.316925 0.464667 0.382003 1138.86 1146.35 1.001
alpha{3} 3.719204 0.709765 2.195823 5.363157 3.608738 867.77 1135.98 1.001
pinvar{all} 0.028333 0.000365 0.000009 0.065581 0.025310 1187.77 1256.50 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 -6178.818422
Model 2: PositiveSelection -6178.818422
Model 0: one-ratio -6184.005542
Model 3: discrete -6108.11488
Model 7: beta -6109.10482
Model 8: beta&w>1 -6109.106913
Model 0 vs 1 10.37423999999919
Model 2 vs 1 0.0
Model 8 vs 7 0.004186000000117929
