--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Tue Dec 19 19:12:18 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_1/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_1/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_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -19864.06 -19906.75
2 -19869.69 -19911.03
--------------------------------------
TOTAL -19864.75 -19910.35
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_1/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_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 6.361077 0.106677 5.703953 6.951266 6.351700 296.49 372.16 1.000
r(A<->C){all} 0.042594 0.000017 0.034776 0.050435 0.042568 716.16 761.38 1.000
r(A<->G){all} 0.173508 0.000091 0.155239 0.191796 0.173197 602.32 602.59 1.000
r(A<->T){all} 0.046588 0.000023 0.036939 0.055144 0.046550 626.63 684.25 1.001
r(C<->G){all} 0.022141 0.000014 0.015154 0.029732 0.021956 701.67 798.03 1.001
r(C<->T){all} 0.685167 0.000168 0.660411 0.710964 0.685467 500.95 540.53 1.000
r(G<->T){all} 0.030001 0.000021 0.021118 0.038880 0.029740 610.93 732.42 1.000
pi(A){all} 0.352567 0.000046 0.339994 0.366552 0.352420 745.99 814.22 1.000
pi(C){all} 0.223430 0.000033 0.212836 0.234730 0.223298 601.96 621.84 1.000
pi(G){all} 0.241908 0.000038 0.229871 0.253928 0.241850 647.01 655.94 1.002
pi(T){all} 0.182095 0.000026 0.172905 0.192450 0.181977 720.17 819.74 1.001
alpha{1,2} 0.187107 0.000060 0.173159 0.203072 0.186852 1115.20 1228.09 1.000
alpha{3} 4.332707 0.456452 3.075915 5.614713 4.273949 1236.62 1368.81 1.000
pinvar{all} 0.119087 0.000268 0.086682 0.151238 0.119062 1099.61 1194.76 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, -18816.636425
