--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Sat Nov 19 00:07:46 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/267/heph-PQ/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/267/heph-PQ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/267/heph-PQ/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/267/heph-PQ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -4602.31 -4625.05
2 -4601.39 -4618.12
--------------------------------------
TOTAL -4601.75 -4624.36
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/267/heph-PQ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/267/heph-PQ/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/267/heph-PQ/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 0.836180 0.004484 0.713225 0.972442 0.832610 983.90 1242.45 1.000
r(A<->C){all} 0.089550 0.000208 0.061020 0.117268 0.088849 1058.34 1123.77 1.000
r(A<->G){all} 0.253958 0.000876 0.193207 0.308745 0.253526 860.46 918.56 1.000
r(A<->T){all} 0.083936 0.000446 0.045029 0.127624 0.082380 866.97 944.17 1.000
r(C<->G){all} 0.052964 0.000094 0.034989 0.072490 0.052519 924.22 1020.70 1.001
r(C<->T){all} 0.442562 0.001249 0.375322 0.513019 0.441897 893.91 918.92 1.001
r(G<->T){all} 0.077030 0.000243 0.047449 0.107919 0.076501 1123.96 1236.53 1.001
pi(A){all} 0.235354 0.000118 0.216044 0.258509 0.235282 1024.87 1082.40 1.000
pi(C){all} 0.329975 0.000135 0.306793 0.351716 0.329827 1079.98 1220.89 1.000
pi(G){all} 0.248699 0.000120 0.228251 0.270516 0.248768 1157.11 1194.00 1.001
pi(T){all} 0.185971 0.000090 0.166892 0.203250 0.185805 1104.39 1171.17 1.001
alpha{1,2} 0.150788 0.000229 0.122431 0.180736 0.149648 1301.95 1401.48 1.000
alpha{3} 4.087019 1.051216 2.158417 6.031862 3.945916 1216.70 1350.23 1.000
pinvar{all} 0.495563 0.000889 0.438677 0.555465 0.496249 918.35 1143.65 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 -4227.346774
Model 2: PositiveSelection -4227.346774
Model 0: one-ratio -4232.966012
Model 3: discrete -4219.192004
Model 7: beta -4219.296233
Model 8: beta&w>1 -4219.297269
Model 0 vs 1 11.238476000000446
Model 2 vs 1 0.0
Model 8 vs 7 0.0020719999993161764
