--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sun Nov 05 04:17:51 WET 2017
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/Ebolaaminoresults/vp30/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/Ebolaaminoresults/vp30/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Ebolaaminoresults/vp30/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/Ebolaaminoresults/vp30/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -4751.12 -4780.50
2 -4747.23 -4781.31
--------------------------------------
TOTAL -4747.90 -4780.99
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/Ebolaaminoresults/vp30/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/Ebolaaminoresults/vp30/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/Ebolaaminoresults/vp30/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 4.356307 0.130923 3.672846 5.063989 4.344487 850.95 1054.60 1.000
r(A<->C){all} 0.136041 0.000347 0.100679 0.172930 0.135140 769.16 809.06 1.001
r(A<->G){all} 0.354106 0.001031 0.293495 0.420005 0.353335 858.83 889.57 1.000
r(A<->T){all} 0.043842 0.000142 0.022236 0.067581 0.043201 890.52 922.05 1.000
r(C<->G){all} 0.019826 0.000150 0.000168 0.042538 0.018121 938.98 1028.91 1.000
r(C<->T){all} 0.389274 0.000984 0.327785 0.451094 0.388475 915.40 940.94 1.000
r(G<->T){all} 0.056911 0.000195 0.032064 0.084312 0.056006 906.58 1007.68 1.000
pi(A){all} 0.326458 0.000134 0.303177 0.348258 0.326550 1052.65 1097.63 1.000
pi(C){all} 0.217235 0.000095 0.198753 0.236868 0.217209 756.31 865.18 1.000
pi(G){all} 0.197941 0.000103 0.178776 0.217571 0.197863 760.84 814.94 1.000
pi(T){all} 0.258366 0.000124 0.235834 0.278525 0.258145 1146.34 1158.38 1.000
alpha{1,2} 0.225329 0.000469 0.185093 0.268446 0.223980 1050.25 1275.62 1.000
alpha{3} 4.191909 0.982136 2.389737 6.100594 4.075852 1356.08 1428.54 1.000
pinvar{all} 0.031281 0.000403 0.000018 0.067993 0.029013 1250.59 1368.20 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 -4260.659656
Model 2: PositiveSelection -4260.659656
Model 0: one-ratio -4322.602681
Model 3: discrete -4206.815233
Model 7: beta -4206.99123
Model 8: beta&w>1 -4206.878591
Model 0 vs 1 123.88605000000098
Model 2 vs 1 0.0
Model 8 vs 7 0.2252779999998893
