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=en&user=iSSbrhwAAAAJ 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/