--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sun May 13 01:28:00 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/NS3_1/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N2/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS3_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/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -14034.54 -14081.15
2 -14034.65 -14078.23
--------------------------------------
TOTAL -14034.59 -14080.51
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N2/NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N2/NS3_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/NS3_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} 7.996487 0.185794 7.149314 8.846762 7.988390 543.38 644.09 1.001
r(A<->C){all} 0.038383 0.000021 0.029729 0.047227 0.038353 721.52 800.96 1.000
r(A<->G){all} 0.188100 0.000142 0.165009 0.211106 0.187959 356.37 419.35 1.000
r(A<->T){all} 0.040573 0.000023 0.031738 0.050365 0.040334 797.30 824.24 1.002
r(C<->G){all} 0.016096 0.000014 0.008840 0.023246 0.015875 727.53 780.20 1.002
r(C<->T){all} 0.692003 0.000223 0.661887 0.718734 0.692027 322.81 410.10 1.001
r(G<->T){all} 0.024844 0.000022 0.015476 0.033641 0.024562 825.30 840.93 1.000
pi(A){all} 0.357829 0.000064 0.342153 0.373484 0.357717 725.17 755.45 1.000
pi(C){all} 0.216198 0.000043 0.204034 0.229648 0.216178 692.29 705.08 1.000
pi(G){all} 0.231022 0.000050 0.218207 0.245644 0.230743 677.20 695.85 1.001
pi(T){all} 0.194951 0.000037 0.182680 0.206027 0.194944 669.47 715.30 1.000
alpha{1,2} 0.157489 0.000045 0.144040 0.170021 0.157265 1175.26 1249.58 1.000
alpha{3} 5.665703 0.830564 4.096319 7.577616 5.564216 1224.90 1282.90 1.001
pinvar{all} 0.124441 0.000298 0.091971 0.159184 0.124127 1179.28 1302.67 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 -13230.463408
Model 2: PositiveSelection -13230.463408
Model 0: one-ratio -13264.227654
Model 3: discrete -13096.500061
Model 7: beta -13083.261299
Model 8: beta&w>1 -13082.522104
Model 0 vs 1 67.52849200000128
Model 2 vs 1 0.0
Model 8 vs 7 1.4783900000002177
