--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Jul 13 07:50:48 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/NS4B_3/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_3/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/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6062.49 -6104.88
2 -6064.49 -6105.84
--------------------------------------
TOTAL -6063.06 -6105.47
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_N3/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_N3/NS4B_3/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/NS4B_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 7.311652 0.244854 6.406078 8.344652 7.300631 756.58 830.02 1.000
r(A<->C){all} 0.038433 0.000049 0.025029 0.051937 0.038178 723.43 871.60 1.000
r(A<->G){all} 0.220040 0.000389 0.183060 0.260135 0.219264 559.12 593.49 1.000
r(A<->T){all} 0.049728 0.000062 0.035067 0.065270 0.049220 796.34 908.41 1.001
r(C<->G){all} 0.028186 0.000060 0.013783 0.043451 0.027653 746.12 759.84 1.000
r(C<->T){all} 0.635106 0.000559 0.592684 0.684394 0.635664 572.51 647.25 1.000
r(G<->T){all} 0.028507 0.000060 0.014180 0.043607 0.028017 728.61 798.72 1.000
pi(A){all} 0.335847 0.000153 0.312087 0.360493 0.335754 727.59 807.00 1.000
pi(C){all} 0.230527 0.000099 0.212034 0.251292 0.230376 837.48 902.30 1.000
pi(G){all} 0.212170 0.000107 0.192292 0.232509 0.212122 810.04 1005.14 1.000
pi(T){all} 0.221455 0.000108 0.200791 0.241913 0.221056 814.97 825.18 1.000
alpha{1,2} 0.182573 0.000165 0.157226 0.206168 0.181750 965.08 1112.92 1.000
alpha{3} 4.927679 0.978321 3.109605 6.881684 4.828890 1479.54 1490.27 1.000
pinvar{all} 0.138518 0.000846 0.081783 0.195865 0.137491 1370.13 1390.18 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 -5568.971649
Model 2: PositiveSelection -5568.971649
Model 0: one-ratio -5591.609224
Model 3: discrete -5504.151449
Model 7: beta -5505.475438
Model 8: beta&w>1 -5504.225466
Model 0 vs 1 45.275149999999485
Model 2 vs 1 0.0
Model 8 vs 7 2.499944000001051
