--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Tue Dec 19 21:39:09 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_2/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_2/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_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -22759.85 -22800.75
2 -22760.11 -22803.18
--------------------------------------
TOTAL -22759.97 -22802.57
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DGA_B3/NS5_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DGA_B3/NS5_2/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_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 7.721383 0.115024 7.030942 8.348635 7.706858 365.90 498.67 1.000
r(A<->C){all} 0.038344 0.000011 0.031640 0.045020 0.038193 662.36 750.03 1.000
r(A<->G){all} 0.206044 0.000101 0.187766 0.225843 0.205760 368.94 389.23 1.000
r(A<->T){all} 0.046190 0.000017 0.038407 0.054461 0.046089 719.86 884.01 1.000
r(C<->G){all} 0.021441 0.000012 0.015036 0.028345 0.021337 507.14 643.29 1.000
r(C<->T){all} 0.660431 0.000158 0.637136 0.685327 0.660542 346.38 385.30 1.000
r(G<->T){all} 0.027549 0.000017 0.019478 0.035397 0.027471 676.66 774.06 1.001
pi(A){all} 0.363059 0.000040 0.350143 0.374927 0.363172 560.39 658.09 1.002
pi(C){all} 0.223394 0.000028 0.213462 0.234309 0.223388 583.99 673.56 1.002
pi(G){all} 0.235058 0.000032 0.224303 0.246688 0.234999 601.16 702.97 1.000
pi(T){all} 0.178490 0.000021 0.169861 0.187944 0.178437 586.84 612.71 1.000
alpha{1,2} 0.187743 0.000057 0.172751 0.202393 0.187514 1030.88 1097.28 1.001
alpha{3} 6.037151 0.828804 4.452672 7.948138 5.935705 1294.61 1397.80 1.000
pinvar{all} 0.138376 0.000207 0.109769 0.166592 0.138274 1108.20 1134.43 1.001
------------------------------------------------------------------------------------------------------
* 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, -22004.768339
