Hi Pas,
K is just a descriptive statistic for tip data on a tree with some specified
branch lengths.
Obviously, if you change the branch lengths (or the topology or the tip data),
then K will be different.
How much different depends on the details.
It is likely that certain branch-length transformations (whether purely
statistical or designed to mimic something like an OU process) will tend to
make K either larger or smaller, at least when checked cross a large number of
examples. Somebody would need to do a lot of simulations to sort this out.
Some related relevant things are here:
Revell, L. J., L. J. Harmon, and D. C. Collar. 2008. Phylogenetic signal,
evolutionary process, and rate. Syst. Biol. 57:591-601.
In the original Blomberg et al. (2003) paper we avoided this issue entirely by
only reporting K using whatever tree the original paper used. We wanted to be
able to compare K values among traits and studies in some sort of simple and
fair way.
If lambda and OU transforms are leading to very different K values (how
different?) that does not mean one K value is better than the other. But it
does mean you would want to be careful if you tried to compare your K value
with other studies that did not use lambda and/or OU transforms.
Cheers,
Ted
Theodore Garland, Jr.
Professor
Department of Biology
University of California, Riverside
Riverside, CA 92521
Office Phone: (951) 827-3524
Wet Lab Phone: (951) 827-5724
Dry Lab Phone: (951) 827-4026
Home Phone: (951) 328-0820
Facsimile: (951) 827-4286 = Dept. office (not confidential)
Email: tgarl...@ucr.edu
http://www.biology.ucr.edu/people/faculty/Garland.html
http://scholar.google.com/citations?hl=enuser=iSSbrhwJ
Experimental Evolution: Concepts, Methods, and Applications of Selection
Experiments. 2009.
Edited by Theodore Garland, Jr. and Michael R. Rose
http://www.ucpress.edu/book.php?isbn=9780520261808
(PDFs of chapters are available from me or from the individual authors)
From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org] on
behalf of pasquale.r...@libero.it [pasquale.r...@libero.it]
Sent: Thursday, January 24, 2013 12:14 PM
To: r-sig-phylo@r-project.org Mailing-list
Subject: [R-sig-phylo] R: Re: From ClustalW2 Tree to Heat Map in R
Hi Gents and Lads,
I have a very rapid question with a perhaps not-so-obvious reply. I'm in the
process of testing a number of evolutionary models and estimating phylogenetic
signal on a certain univariate data set. So something very basic and very
simple. The point is, I found BM performs poorly as compared to OU (single
peak) and lambda. Thus, I transformed the tree by using the fitted lamdba
and/or alpha before calculating Blomberg et al's K statistic. Does this make
sense?
If yes, the competing models have similar Akaike weigths (OU = 0.5, lambda =
0.3) but give very different estimates of K when their fitted parameters are
used to transform the tree branch lenghts. How does discriminate which K
estimate is best?
Translating in R-esque:
require(geiger)
require(phytools)
fitContinuous(tree, x, model=OU) ## gives relatively low alpha (.07)
phylosig(ouTree(tree,alpha=alpha),x,method =K, test =T, nsim =1000) ## gives
very low K
fitContinuous(tree, x, model=lambda) ## gives very high lambda (.95)
phylosig(lambdaTree(tree,lambda=lambda),x,method =K, test =T, nsim =1000) ##
gives very high K
thanks for help,
Pas
___
R-sig-phylo mailing list - R-sig-phylo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
Searchable archive at http://www.mail-archive.com/r-sig-phylo@r-project.org/
___
R-sig-phylo mailing list - R-sig-phylo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
Searchable archive at http://www.mail-archive.com/r-sig-phylo@r-project.org/
