--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sun Jul 15 16:39:02 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_4/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/prM_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/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -4194.45 -4234.85
2 -4190.64 -4240.11
--------------------------------------
TOTAL -4191.31 -4239.42
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/prM_4/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/prM_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/prM_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} 6.997234 0.283086 5.958965 8.023488 6.983296 643.34 942.66 1.000
r(A<->C){all} 0.040342 0.000074 0.024139 0.057363 0.039951 906.65 955.27 1.000
r(A<->G){all} 0.189127 0.000497 0.145193 0.229938 0.189010 543.26 647.83 1.000
r(A<->T){all} 0.060547 0.000121 0.038913 0.081604 0.060061 950.94 961.27 1.000
r(C<->G){all} 0.022341 0.000056 0.008633 0.036798 0.021847 792.87 904.59 1.001
r(C<->T){all} 0.651113 0.000797 0.596612 0.706436 0.651107 477.95 648.26 1.000
r(G<->T){all} 0.036531 0.000101 0.018678 0.056452 0.035896 790.10 830.00 1.001
pi(A){all} 0.300643 0.000217 0.272338 0.328294 0.300586 912.73 976.66 1.000
pi(C){all} 0.250444 0.000180 0.225358 0.278139 0.250259 762.65 763.96 1.000
pi(G){all} 0.239497 0.000216 0.210454 0.266969 0.239141 821.35 835.78 1.000
pi(T){all} 0.209416 0.000140 0.186480 0.233125 0.209175 862.16 941.38 1.000
alpha{1,2} 0.196338 0.000267 0.164671 0.228289 0.195265 1149.25 1242.09 1.000
alpha{3} 3.724688 0.688380 2.257511 5.427526 3.624487 1402.51 1451.76 1.000
pinvar{all} 0.047002 0.000788 0.000020 0.097018 0.044753 1410.60 1455.80 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 -3953.082254
Model 2: PositiveSelection -3953.082254
Model 0: one-ratio -3966.810545
Model 3: discrete -3919.447424
Model 7: beta -3921.588518
Model 8: beta&w>1 -3921.589525
Model 0 vs 1 27.4565819999998
Model 2 vs 1 0.0
Model 8 vs 7 0.002013999999689986
