Dear Julien, I'll just add two other papers to your reading list (both available at my web page):
Garland, T., Jr., A. W. Dickerman, C. M. Janis, and J. A. Jones. 1993. Phylogenetic analysis of covariance by computer simulation. Systematic Biology 42:265-292. And the Appendix of this paper: Lavin, S. R., W. H. Karasov, A. R. Ives, K. M. Middleton, and T. Garland, Jr. 2008. Morphometrics of the avian small intestine, compared with non-flying mammals: A phylogenetic perspective. Physiological and Biochemical Zoology 81:526-550. [provides Matlab Regressionv2.m, released as part of the PHYSIG package] 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 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 Marguerite Butler [mbutler...@gmail.com] Sent: Wednesday, May 16, 2012 12:27 PM To: Julien Lorion Cc: r-sig-phylo@r-project.org Subject: Re: [R-sig-phylo] Best way to test correlation between discrete and continuous variables ? Dear Julien, There is no problem with applying an ANOVA within a phylogenetic framework. This is essentially phylogenetic GLS, which you can implement easily with APE. You can have a look at Emmanuel's book (which was just recently came out in the second edition Nov. 2011, by the way). http://www.amazon.com/Analysis-Phylogenetics-Evolution-Emmanuel-Paradis/dp/1461417422/ref=sr_ob_11?s=books&ie=UTF8&qid=1337196146&sr=1-11 In essence, you are looking at the phylogeny as a source of "correlated errors" which you are "correcting for" under some assumed model of evolution -- either Brownian motion or Ornstein Ulenbeck. It is viewed as noise which is controlled for in order to see the pattern from ecology, etc. The mechanics of how to incorporate the phylogenetic covariance matrix into the linear model is explained in the appendix of my paper: Butler M.A. Schoener T.W., and Losos J.B. (2000) The relationship between habitat type and sexual size dimorphism in Greater Antillean Anolis lizards. Evolution 54(1):259-272. DOI: http://dx.doi.org/10.1554/0014-3820(2000)054[0259:TRBSSD]2.0.CO;2 Another approach to analyzing the same kind of data is to view the evolution of the quantitative character as being influenced by a number of factors (for example, habitat, symbionts, etc.), which can be thought of as "selective regimes" which influence the evolution of body size. You can then create explicit biological hypotheses which are translated to mathematical models, and test these hypotheses against each other for the best explanation of the data. This approach has software package developed for it called "OUCH" which is available in R. It is explained and illustrated in this paper: Butler M.A. and King A.A. (2004) Phylogenetic comparative analysis: a modeling approach for adaptive evolution. The American Naturalist 164(6):683-695. DOI: 10.1086/426002 Appologies for the shameless self-promotion:). Marguerite On May 15, 2012, at 9:53 PM, Julien Lorion wrote: > Dear all, > > I am working on the evolution of deep-sea symbiotic mussels... I have got a > tree and 5 characters: habitat (hydrothermal vents, cold seep and organic > substrate), presence/absence of methanotrophic symbionts, presence/absence of > sulfoxydizing symbionts, symbiont location (extra VS intracellular) and body > length... > > So that's 1 continuous and 4 discrete binary variables (actually, I assumed > vent and seeps are very similar... so no need to take into account the 3 > states) > > At first I tested various hypotheses about correlation between my discrete > characters... I chose the easy way: I remembered my master lectures and used > basic Pagel's correlations. If you think that any new tool performs better, > I'd be happy to hear it. > > For now, my main concern is that I wanna test the impact of two binary > variables (habitat and symbiont location) on the body length... In fact, that > looks likes ANOVAs from which I wanna remove the phylogenetic bias... > > The point is that I don't know how to do that in practice. May someone have > some advices ? > > Thanks by advance > > Best regards > > Julien > > _______________________________________________ > R-sig-phylo mailing list > R-sig-phylo@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-phylo ____________________________________________ Marguerite A. Butler Associate Professor Department of Biology University of Hawaii 2450 Campus Rd., Dean Hall Rm. 2 Honolulu, HI 96822 Office: 808-956-4713 Dept: 808-956-8617 Lab: 808-956-5867 FAX: 808-956-9812 http://www.hawaii.edu/zoology/faculty/butler.html http://www2.hawaii.edu/~mbutler http://www.hawaii.edu/zoology/ [[alternative HTML version deleted]] _______________________________________________ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo _______________________________________________ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
