--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu May 31 07:29:13 WEST 2018
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=MUSCLE
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb_adops
tcoffee.bin=t_coffee_ADOPS
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS1/DNG_A1/NS2A_3/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS2A_3/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/ADOPS1/DNG_A1/NS2A_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -7651.79 -7706.68
2 -7652.72 -7702.79
--------------------------------------
TOTAL -7652.15 -7706.01
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS1/DNG_A1/NS2A_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS1/DNG_A1/NS2A_3/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/ADOPS1/DNG_A1/NS2A_3/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 10.708158 0.506082 9.325163 12.085060 10.670070 712.81 782.59 1.000
r(A<->C){all} 0.049607 0.000063 0.034672 0.065998 0.049398 779.48 808.99 1.002
r(A<->G){all} 0.244089 0.000327 0.209844 0.280030 0.243436 565.75 567.53 1.003
r(A<->T){all} 0.046806 0.000047 0.032799 0.059534 0.046482 771.57 917.46 1.001
r(C<->G){all} 0.034281 0.000063 0.019848 0.050749 0.034049 589.02 710.67 1.000
r(C<->T){all} 0.589565 0.000464 0.545501 0.628685 0.590270 500.21 512.35 1.003
r(G<->T){all} 0.035653 0.000053 0.022110 0.050254 0.035356 820.31 878.36 1.000
pi(A){all} 0.310590 0.000119 0.288218 0.330565 0.310709 855.33 882.73 1.000
pi(C){all} 0.206980 0.000084 0.189792 0.224857 0.206842 575.13 706.45 1.000
pi(G){all} 0.239191 0.000099 0.221005 0.260202 0.238909 713.15 794.33 1.001
pi(T){all} 0.243239 0.000103 0.225059 0.264341 0.243060 790.72 822.12 1.002
alpha{1,2} 0.401019 0.001716 0.328601 0.488603 0.396587 1205.41 1219.01 1.001
alpha{3} 4.940137 1.058605 3.092832 6.899818 4.842345 1012.36 1167.00 1.000
pinvar{all} 0.034583 0.000396 0.000017 0.070242 0.031735 1169.72 1219.17 1.002
------------------------------------------------------------------------------------------------------
* 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 1: NearlyNeutral -7383.430627
Model 2: PositiveSelection -7383.430627
Model 0: one-ratio -7388.515064
Model 3: discrete -7300.767982
Model 7: beta -7302.928315
Model 8: beta&w>1 -7302.929901
Model 0 vs 1 10.16887400000087
Model 2 vs 1 0.0
Model 8 vs 7 0.0031720000006316695
