--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Wed Dec 20 00:16:15 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_3/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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/ADOPS/DGA_B3/NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -22634.19 -22683.08
2 -22632.55 -22672.67
--------------------------------------
TOTAL -22633.07 -22682.38
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_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/ADOPS/DGA_B3/NS5_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} 7.037542 0.097834 6.395721 7.609735 7.030455 578.24 617.18 1.000
r(A<->C){all} 0.042441 0.000013 0.035781 0.049905 0.042350 773.35 784.55 1.000
r(A<->G){all} 0.186218 0.000087 0.169674 0.206261 0.186328 417.78 462.68 1.000
r(A<->T){all} 0.044348 0.000017 0.036675 0.052578 0.044256 833.11 867.77 1.003
r(C<->G){all} 0.025629 0.000013 0.018868 0.032974 0.025496 649.03 708.10 1.000
r(C<->T){all} 0.672155 0.000152 0.648429 0.695746 0.672036 320.23 409.76 1.000
r(G<->T){all} 0.029208 0.000018 0.021337 0.037763 0.029085 604.95 645.87 1.001
pi(A){all} 0.357967 0.000044 0.345457 0.371441 0.358113 760.35 864.55 1.001
pi(C){all} 0.222637 0.000030 0.211813 0.233332 0.222653 784.96 814.45 1.000
pi(G){all} 0.239866 0.000036 0.227339 0.250895 0.239847 537.16 597.14 1.000
pi(T){all} 0.179530 0.000022 0.170567 0.189439 0.179510 579.89 703.03 1.000
alpha{1,2} 0.200829 0.000065 0.185507 0.216860 0.200509 1342.45 1421.72 1.000
alpha{3} 6.169726 0.826998 4.494364 7.974510 6.056387 1125.57 1313.29 1.000
pinvar{all} 0.129875 0.000211 0.102624 0.159955 0.129611 1315.55 1320.75 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, -21894.990207
