--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Fri Nov 25 00:59:00 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/30/CadN-PC/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/30/CadN-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/30/CadN-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/30/CadN-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -31171.24 -31188.70
2 -31171.74 -31186.66
--------------------------------------
TOTAL -31171.46 -31188.13
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/30/CadN-PC/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/30/CadN-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/30/CadN-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} 1.189595 0.000931 1.133053 1.252446 1.188950 1410.92 1455.96 1.000
r(A<->C){all} 0.082354 0.000029 0.072153 0.093428 0.082244 978.32 1108.31 1.001
r(A<->G){all} 0.295840 0.000109 0.273485 0.315164 0.295598 702.09 756.34 1.002
r(A<->T){all} 0.069888 0.000030 0.060169 0.081398 0.069806 1047.05 1063.25 1.001
r(C<->G){all} 0.056879 0.000018 0.048792 0.065396 0.056788 869.67 989.98 1.000
r(C<->T){all} 0.440788 0.000125 0.418677 0.462162 0.440747 559.01 661.98 1.002
r(G<->T){all} 0.054252 0.000020 0.045356 0.063237 0.054095 901.03 1023.86 1.000
pi(A){all} 0.253458 0.000019 0.244998 0.262244 0.253323 697.27 840.55 1.000
pi(C){all} 0.261944 0.000018 0.253629 0.269772 0.261936 661.84 706.34 1.000
pi(G){all} 0.266981 0.000019 0.258335 0.275215 0.266916 497.45 797.75 1.000
pi(T){all} 0.217617 0.000015 0.209741 0.225156 0.217544 632.87 809.01 1.001
alpha{1,2} 0.085978 0.000009 0.080313 0.091878 0.085898 1439.94 1470.47 1.000
alpha{3} 8.213413 1.628749 5.921812 10.713210 8.106510 1296.62 1311.23 1.000
pinvar{all} 0.438154 0.000120 0.416767 0.459369 0.438205 1486.78 1493.89 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 -28979.626918
Model 2: PositiveSelection -28979.626938
Model 0: one-ratio -29045.783047
Model 3: discrete -28949.183788
Model 7: beta -28959.628256
Model 8: beta&w>1 -28957.150338
Model 0 vs 1 132.3122579999981
Model 2 vs 1 3.9999998989515007E-5
Model 8 vs 7 4.955836000001
