--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu Jan 23 09:44:04 GMT 2020
codeml.models=0 1 2 7 8
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=/opt/mrbayes_3.2.2/src
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/data/1res/adhE2/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/data/1res/adhE2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/1res/adhE2/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 /data/1res/adhE2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -1470.09 -1473.55
2 -1470.11 -1473.29
--------------------------------------
TOTAL -1470.10 -1473.43
--------------------------------------
Model parameter summaries over the runs sampled in files
"/data/1res/adhE2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/data/1res/adhE2/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 "/data/1res/adhE2/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.897627 0.091383 0.345431 1.506139 0.865571 1302.52 1401.76 1.000
r(A<->C){all} 0.169711 0.020798 0.000085 0.462745 0.131429 237.32 292.57 1.009
r(A<->G){all} 0.171098 0.020941 0.000011 0.461043 0.131861 171.91 195.72 1.000
r(A<->T){all} 0.171830 0.018975 0.000129 0.447164 0.139122 135.22 169.60 1.005
r(C<->G){all} 0.155252 0.018268 0.000026 0.428926 0.117615 205.00 270.61 1.000
r(C<->T){all} 0.158533 0.019276 0.000015 0.445012 0.117438 113.13 181.99 1.000
r(G<->T){all} 0.173576 0.020549 0.000050 0.453254 0.137118 172.37 196.09 1.005
pi(A){all} 0.196143 0.000146 0.172586 0.218871 0.196155 1332.27 1416.64 1.000
pi(C){all} 0.309763 0.000206 0.282501 0.338219 0.309691 1012.62 1232.80 1.000
pi(G){all} 0.311957 0.000192 0.285288 0.338180 0.311749 1402.44 1435.41 1.000
pi(T){all} 0.182137 0.000136 0.160028 0.204982 0.182048 1501.00 1501.00 1.000
alpha{1,2} 0.430139 0.235415 0.000215 1.385599 0.268271 889.56 965.83 1.001
alpha{3} 0.451137 0.227718 0.000548 1.404458 0.295273 1163.63 1218.51 1.000
pinvar{all} 0.998609 0.000003 0.995637 0.999999 0.999134 1284.34 1329.58 1.001
------------------------------------------------------------------------------------------------------
* 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 -1397.230031
Model 2: PositiveSelection -1397.230031
Model 0: one-ratio -1397.230031
Model 7: beta -1397.230031
Model 8: beta&w>1 -1397.230031
Model 0 vs 1 0.0
Model 2 vs 1 0.0
Model 8 vs 7 0.0
