--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Mon Feb 15 18:40:10 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_1/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/Z_B1/Zika-NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Z_B1/Zika-NS3_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/Z_B1/Zika-NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -4290.12 -4344.83
2 -4288.75 -4358.34
--------------------------------------
TOTAL -4289.22 -4357.65
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/Z_B1/Zika-NS3_1/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/Z_B1/Zika-NS3_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/Z_B1/Zika-NS3_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} 0.903752 0.012935 0.705603 1.143963 0.891314 387.28 420.76 1.000
r(A<->C){all} 0.019023 0.000052 0.006685 0.033874 0.018367 521.16 609.38 1.001
r(A<->G){all} 0.268087 0.001994 0.189393 0.362198 0.266993 310.27 431.65 1.000
r(A<->T){all} 0.015838 0.000057 0.002340 0.030218 0.014681 541.64 707.15 1.000
r(C<->G){all} 0.006916 0.000018 0.000484 0.015554 0.006160 873.43 891.48 1.000
r(C<->T){all} 0.664737 0.002362 0.563381 0.752409 0.665257 294.56 395.27 1.000
r(G<->T){all} 0.025398 0.000080 0.009583 0.043789 0.024597 750.64 818.10 1.000
pi(A){all} 0.281122 0.000099 0.261962 0.300419 0.281192 1050.74 1182.86 1.000
pi(C){all} 0.230149 0.000086 0.212020 0.247698 0.230138 881.59 970.07 1.000
pi(G){all} 0.280475 0.000096 0.261942 0.300056 0.280172 1075.68 1127.92 1.002
pi(T){all} 0.208255 0.000075 0.192267 0.225421 0.208298 1044.24 1169.25 1.000
alpha{1,2} 0.041711 0.000522 0.000168 0.075718 0.043404 1088.72 1108.40 1.000
alpha{3} 3.603297 0.972820 1.874561 5.533610 3.468452 1183.99 1279.52 1.000
pinvar{all} 0.451326 0.000972 0.389857 0.510911 0.451929 1346.32 1360.00 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, -4021.142799
