--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Thu Nov 10 18:06:32 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/191/CG8303-PD/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/191/CG8303-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/191/CG8303-PD/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/191/CG8303-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6052.18 -6068.56
2 -6051.92 -6068.98
--------------------------------------
TOTAL -6052.04 -6068.79
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/191/CG8303-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/191/CG8303-PD/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/191/CG8303-PD/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.376891 0.007187 1.212918 1.539654 1.375829 1231.25 1283.81 1.001
r(A<->C){all} 0.095972 0.000175 0.071688 0.122512 0.095375 1147.73 1176.08 1.001
r(A<->G){all} 0.267687 0.000615 0.221187 0.317743 0.266431 807.16 838.83 1.000
r(A<->T){all} 0.065579 0.000194 0.039232 0.091536 0.064894 827.71 898.20 1.000
r(C<->G){all} 0.073981 0.000097 0.054615 0.092158 0.073664 1120.48 1193.96 1.000
r(C<->T){all} 0.443049 0.000757 0.387428 0.493139 0.442460 744.37 810.86 1.000
r(G<->T){all} 0.053733 0.000108 0.034534 0.075514 0.053310 1078.67 1196.18 1.000
pi(A){all} 0.213731 0.000095 0.193974 0.232410 0.213655 863.16 975.51 1.000
pi(C){all} 0.299860 0.000108 0.280379 0.321254 0.299759 1056.21 1064.10 1.000
pi(G){all} 0.263793 0.000106 0.244780 0.284461 0.263477 1049.53 1079.71 1.000
pi(T){all} 0.222616 0.000083 0.204745 0.240286 0.222585 1205.39 1239.35 1.000
alpha{1,2} 0.104280 0.000066 0.089210 0.120185 0.103947 1174.97 1337.98 1.000
alpha{3} 3.687562 0.720289 2.266047 5.393253 3.575785 1361.35 1431.18 1.000
pinvar{all} 0.384432 0.000809 0.328207 0.440031 0.385335 1410.93 1455.97 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 -5574.601456
Model 2: PositiveSelection -5574.601479
Model 0: one-ratio -5595.505515
Model 3: discrete -5548.157414
Model 7: beta -5548.298229
Model 8: beta&w>1 -5547.921762
Model 0 vs 1 41.80811799999901
Model 2 vs 1 4.599999920174014E-5
Model 8 vs 7 0.7529340000000957
