--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Tue Nov 22 00:46:47 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/3/AcCoAS-PB/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/3/AcCoAS-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/AcCoAS-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/3/AcCoAS-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -5584.69 -5600.22
2 -5584.55 -5600.60
--------------------------------------
TOTAL -5584.62 -5600.43
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/3/AcCoAS-PB/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/AcCoAS-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/3/AcCoAS-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} 1.288775 0.006393 1.132147 1.444876 1.288399 1182.85 1341.93 1.000
r(A<->C){all} 0.100231 0.000231 0.072981 0.130568 0.099263 952.89 1073.81 1.000
r(A<->G){all} 0.250775 0.000588 0.206710 0.302253 0.250154 1074.14 1083.19 1.000
r(A<->T){all} 0.110192 0.000407 0.072614 0.151121 0.109403 1016.51 1114.87 1.000
r(C<->G){all} 0.049593 0.000066 0.033869 0.065552 0.049290 978.57 1065.53 1.000
r(C<->T){all} 0.419698 0.000749 0.366935 0.473918 0.419220 774.89 901.43 1.000
r(G<->T){all} 0.069511 0.000135 0.048232 0.093220 0.069159 1034.08 1155.61 1.001
pi(A){all} 0.197824 0.000092 0.178112 0.216090 0.197456 1001.50 1037.98 1.000
pi(C){all} 0.292759 0.000108 0.272884 0.312800 0.292619 1008.47 1057.27 1.000
pi(G){all} 0.300240 0.000120 0.278780 0.321337 0.300212 950.20 1025.58 1.000
pi(T){all} 0.209178 0.000088 0.189677 0.227180 0.208859 1043.90 1095.76 1.000
alpha{1,2} 0.102111 0.000056 0.087636 0.116346 0.101816 1190.71 1213.01 1.000
alpha{3} 4.341082 0.924845 2.662822 6.215105 4.226608 1098.21 1299.61 1.000
pinvar{all} 0.359356 0.000846 0.303228 0.417332 0.359921 1135.31 1318.15 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 -5139.879125
Model 2: PositiveSelection -5139.879125
Model 0: one-ratio -5163.544282
Model 3: discrete -5138.1288
Model 7: beta -5144.745954
Model 8: beta&w>1 -5138.502955
Model 0 vs 1 47.33031399999891
Model 2 vs 1 0.0
Model 8 vs 7 12.485998000000109
Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: D_melanogaster_AcCoAS-PB)
Pr(w>1) post mean +- SE for w
276 Y 1.000** 1.165
Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118)
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: D_melanogaster_AcCoAS-PB)
Pr(w>1) post mean +- SE for w
276 Y 0.661 1.500 +- 0.921
