--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Mon Dec 05 05:03:59 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
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/ADOPS/361/qkr58E-1-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/361/qkr58E-1-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/361/qkr58E-1-PA/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/ADOPS/361/qkr58E-1-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -3780.46 -3797.08
2 -3781.36 -3799.64
--------------------------------------
TOTAL -3780.81 -3799.02
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/361/qkr58E-1-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/361/qkr58E-1-PA/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/ADOPS/361/qkr58E-1-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.065359 0.006915 0.912972 1.234227 1.061439 1138.71 1251.21 1.000
r(A<->C){all} 0.084524 0.000215 0.057291 0.114546 0.083660 979.43 984.54 1.001
r(A<->G){all} 0.276967 0.000970 0.215801 0.335960 0.275847 754.18 874.83 1.000
r(A<->T){all} 0.096056 0.000643 0.048911 0.145515 0.094425 902.23 918.51 1.001
r(C<->G){all} 0.032987 0.000056 0.017822 0.047004 0.032502 785.38 911.57 1.000
r(C<->T){all} 0.454792 0.001279 0.385721 0.522934 0.455275 747.79 881.13 1.000
r(G<->T){all} 0.054675 0.000200 0.030181 0.084598 0.053848 1147.23 1161.36 1.000
pi(A){all} 0.258130 0.000153 0.230932 0.279456 0.257988 1126.00 1146.05 1.000
pi(C){all} 0.313262 0.000161 0.288246 0.337793 0.312989 1147.90 1223.30 1.001
pi(G){all} 0.261711 0.000149 0.239230 0.286174 0.261419 1067.67 1083.76 1.000
pi(T){all} 0.166896 0.000095 0.148178 0.186131 0.166617 1114.44 1118.16 1.000
alpha{1,2} 0.067527 0.000450 0.011598 0.096363 0.073010 1099.57 1120.10 1.002
alpha{3} 4.120022 1.027653 2.304547 6.102269 3.991260 1323.96 1392.79 1.001
pinvar{all} 0.366686 0.001423 0.288469 0.435804 0.366860 1126.31 1179.58 1.002
------------------------------------------------------------------------------------------------------
* 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 -3489.220768
Model 2: PositiveSelection -3489.218787
Model 0: one-ratio -3489.218787
Model 3: discrete -3488.479275
Model 7: beta -3488.491923
Model 8: beta&w>1 -3488.495866
Model 0 vs 1 0.003962000000683474
Model 2 vs 1 0.003962000000683474
Model 8 vs 7 0.007886000000326021
