--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 18 20:29:02 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
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/ADOPS/274/Hsc70-3-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-3-PC/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/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -5363.20 -5379.40
2 -5363.08 -5383.35
--------------------------------------
TOTAL -5363.14 -5382.68
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/274/Hsc70-3-PC/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/274/Hsc70-3-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.676422 0.002202 0.587626 0.768165 0.674507 1354.94 1371.63 1.000
r(A<->C){all} 0.051050 0.000129 0.030719 0.073907 0.050361 834.53 964.47 1.000
r(A<->G){all} 0.175997 0.000597 0.130049 0.225277 0.175568 756.28 919.88 1.000
r(A<->T){all} 0.054288 0.000278 0.021413 0.085922 0.052965 897.15 1019.01 1.001
r(C<->G){all} 0.056226 0.000077 0.039697 0.073440 0.055778 1081.91 1195.00 1.000
r(C<->T){all} 0.604434 0.000981 0.540164 0.661228 0.604250 776.05 874.70 1.000
r(G<->T){all} 0.058004 0.000130 0.035226 0.079707 0.057265 1188.55 1207.46 1.000
pi(A){all} 0.226782 0.000090 0.209088 0.246017 0.226620 835.02 941.83 1.000
pi(C){all} 0.292682 0.000091 0.274187 0.310665 0.292539 1229.50 1248.25 1.001
pi(G){all} 0.292272 0.000099 0.272858 0.311793 0.292265 920.62 1030.85 1.000
pi(T){all} 0.188264 0.000069 0.171652 0.203455 0.188174 888.46 940.97 1.000
alpha{1,2} 0.033267 0.000411 0.000184 0.067247 0.031786 855.54 874.36 1.000
alpha{3} 4.123766 0.991690 2.425675 6.119612 4.017863 1337.91 1363.59 1.000
pinvar{all} 0.511172 0.000695 0.459691 0.563002 0.511903 1247.68 1374.34 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 1: NearlyNeutral -4932.66204
Model 2: PositiveSelection -4932.859411
Model 0: one-ratio -4932.85941
Model 3: discrete -4932.136197
Model 7: beta -4932.138108
Model 8: beta&w>1 -4932.140858
Model 0 vs 1 0.39473999999972875
Model 2 vs 1 0.3947420000004058
Model 8 vs 7 0.005499999999301508
