--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed Dec 20 05:36:06 WET 2017
codeml.models=
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=MUSCLE
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=/usr/bin/
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb
tcoffee.bin=t_coffee
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/DGA_B3/NS5_5/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_5/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/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -23288.12 -23323.87
2 -23288.87 -23329.17
--------------------------------------
TOTAL -23288.42 -23328.48
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_5/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/DGA_B3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 8.061799 0.129426 7.374975 8.768002 8.044148 406.71 489.73 1.000
r(A<->C){all} 0.035072 0.000010 0.028731 0.041246 0.035008 378.86 605.98 1.000
r(A<->G){all} 0.194707 0.000095 0.175852 0.213502 0.194346 364.83 369.54 1.000
r(A<->T){all} 0.043532 0.000015 0.035703 0.050999 0.043615 832.63 858.04 1.000
r(C<->G){all} 0.022492 0.000011 0.016124 0.028837 0.022345 807.43 841.25 1.002
r(C<->T){all} 0.680304 0.000147 0.657529 0.704235 0.680692 277.45 310.09 1.000
r(G<->T){all} 0.023893 0.000016 0.016436 0.031805 0.023793 569.19 675.45 1.001
pi(A){all} 0.365063 0.000042 0.351920 0.376659 0.365069 532.43 650.61 1.000
pi(C){all} 0.224436 0.000028 0.214117 0.234494 0.224285 590.99 613.37 1.000
pi(G){all} 0.231947 0.000033 0.220742 0.242907 0.232079 578.71 691.51 1.000
pi(T){all} 0.178554 0.000024 0.169176 0.188422 0.178432 396.28 464.12 1.000
alpha{1,2} 0.189319 0.000053 0.175460 0.203537 0.189102 1264.18 1306.72 1.000
alpha{3} 6.620637 0.912778 4.852459 8.529687 6.546054 1382.33 1441.67 1.000
pinvar{all} 0.138172 0.000205 0.109989 0.166131 0.138298 938.31 1027.36 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: One dN/dS ratio for branches, -22524.808358
