--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Tue Nov 29 16:38:20 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/59/CG13024-PB/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/59/CG13024-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/59/CG13024-PB/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/59/CG13024-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -2426.96 -2443.86
2 -2427.10 -2444.07
--------------------------------------
TOTAL -2427.03 -2443.97
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/59/CG13024-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/59/CG13024-PB/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/59/CG13024-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.004648 0.012456 0.806620 1.234269 0.996298 1217.83 1320.82 1.000
r(A<->C){all} 0.089564 0.000428 0.050870 0.129398 0.087875 915.11 998.83 1.000
r(A<->G){all} 0.210864 0.001282 0.141135 0.280922 0.208585 839.39 864.07 1.000
r(A<->T){all} 0.101494 0.000852 0.047083 0.160701 0.099267 1020.98 1057.71 1.000
r(C<->G){all} 0.084672 0.000297 0.051391 0.118019 0.083938 802.53 954.78 1.000
r(C<->T){all} 0.464835 0.002383 0.370195 0.559038 0.465560 624.50 681.68 1.000
r(G<->T){all} 0.048571 0.000370 0.012783 0.085004 0.046742 994.58 1075.27 1.000
pi(A){all} 0.244072 0.000236 0.213065 0.273137 0.243804 681.79 849.37 1.000
pi(C){all} 0.318011 0.000238 0.288030 0.347349 0.317587 1174.18 1208.64 1.000
pi(G){all} 0.262192 0.000232 0.232789 0.291849 0.262020 992.08 1079.31 1.000
pi(T){all} 0.175725 0.000163 0.149717 0.199258 0.175639 1051.85 1153.16 1.000
alpha{1,2} 0.124867 0.000373 0.089709 0.162963 0.123570 1280.41 1339.82 1.003
alpha{3} 2.846692 0.792181 1.321923 4.649449 2.735073 1240.40 1355.95 1.000
pinvar{all} 0.454350 0.002338 0.353485 0.541223 0.456702 1040.04 1199.42 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 -2075.381039
Model 2: PositiveSelection -2075.381039
Model 0: one-ratio -2085.143498
Model 3: discrete -2072.665669
Model 7: beta -2074.670976
Model 8: beta&w>1 -2072.86893
Model 0 vs 1 19.52491800000007
Model 2 vs 1 0.0
Model 8 vs 7 3.604091999999582
