--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Mon Feb 15 19:08:31 WET 2016
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/Z_B1/Zika-NS3_2/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/Z_B1/Zika-NS3_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Z_B1/Zika-NS3_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/Z_B1/Zika-NS3_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -4402.80 -4466.05
2 -4404.47 -4462.07
--------------------------------------
TOTAL -4403.32 -4465.37
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/Z_B1/Zika-NS3_2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Z_B1/Zika-NS3_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/Z_B1/Zika-NS3_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} 0.982999 0.013908 0.777034 1.222952 0.971574 410.29 459.15 1.001
r(A<->C){all} 0.025146 0.000067 0.010116 0.041506 0.024460 640.81 645.74 1.000
r(A<->G){all} 0.299723 0.002002 0.219048 0.390608 0.297725 451.45 475.88 1.002
r(A<->T){all} 0.015869 0.000061 0.002011 0.030487 0.014829 608.66 670.29 1.000
r(C<->G){all} 0.004831 0.000014 0.000004 0.012245 0.003896 788.01 874.39 1.001
r(C<->T){all} 0.637476 0.002160 0.546507 0.727567 0.639326 432.81 455.65 1.002
r(G<->T){all} 0.016955 0.000055 0.003709 0.031524 0.015880 770.95 771.99 1.001
pi(A){all} 0.283263 0.000098 0.263535 0.301518 0.283373 1028.56 1079.58 1.000
pi(C){all} 0.232230 0.000083 0.214209 0.250014 0.232116 1123.40 1156.76 1.000
pi(G){all} 0.279925 0.000095 0.259403 0.297168 0.279763 1106.60 1244.93 1.001
pi(T){all} 0.204583 0.000074 0.188206 0.221631 0.204724 1008.95 1090.89 1.001
alpha{1,2} 0.035676 0.000436 0.000102 0.068462 0.035970 834.34 927.19 1.000
alpha{3} 3.547942 0.860756 1.986264 5.320641 3.447681 1383.34 1442.17 1.000
pinvar{all} 0.437282 0.000975 0.378356 0.498432 0.438521 988.00 1154.01 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, -4152.689471
