--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu May 03 23:16:31 WEST 2018
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/DNGB3/NS5_5/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_5/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/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -20308.63 -20359.61
2 -20311.87 -20346.48
--------------------------------------
TOTAL -20309.28 -20358.92
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/DNGB3/NS5_5/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/DNGB3/NS5_5/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 6.531718 0.109004 5.914085 7.197690 6.521873 410.83 417.93 1.004
r(A<->C){all} 0.042863 0.000016 0.035378 0.050781 0.042826 728.28 790.35 1.000
r(A<->G){all} 0.185676 0.000095 0.166779 0.204497 0.185822 443.92 445.33 1.000
r(A<->T){all} 0.043253 0.000020 0.034707 0.052235 0.043331 500.84 653.51 1.000
r(C<->G){all} 0.028639 0.000017 0.020885 0.036806 0.028488 777.07 839.15 1.000
r(C<->T){all} 0.676374 0.000172 0.652171 0.703560 0.676458 396.06 407.46 1.000
r(G<->T){all} 0.023194 0.000019 0.014690 0.031119 0.023106 677.38 707.56 1.000
pi(A){all} 0.356881 0.000049 0.342716 0.370494 0.357050 809.95 824.91 1.000
pi(C){all} 0.219329 0.000029 0.209532 0.230181 0.219213 828.70 864.42 1.001
pi(G){all} 0.240595 0.000038 0.229385 0.253429 0.240683 693.14 763.98 1.003
pi(T){all} 0.183195 0.000027 0.173244 0.193327 0.183210 601.17 649.10 1.000
alpha{1,2} 0.186403 0.000060 0.170810 0.201248 0.186128 1135.38 1240.32 1.000
alpha{3} 5.000369 0.604936 3.613205 6.474755 4.910508 1236.26 1314.68 1.000
pinvar{all} 0.122852 0.000240 0.092680 0.152978 0.122416 1231.02 1232.72 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, -17822.477632
