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Bioinformatics Advance Access originally published online on February 21, 2008
Bioinformatics 2008 24(7):1018-1020; doi:10.1093/bioinformatics/btn065
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

PCCA: a program for phylogenetic canonical correlation analysis

Liam J. Revell * and Alexis S. Harrison

Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA

*To whom correspondence should be addressed.


  Abstract

Summary: PCCA (phylogenetic canonical correlation analysis) is a new program for canonical correlation analysis of multivariate, continuously valued data from biological species. Canonical correlation analysis is a technique in which derived variables are obtained from two sets of original variables whereby the correlations between corresponding derived variables are maximized. It is a very useful multivariate statistical method for the calculation and analysis of correlations between character sets. The program controls for species non-independence due to phylogenetic history and computes canonical coefficients, correlations and scores; and conducts hypothesis tests on the canonical correlations. It can also compute a multivariate version of Pagel's {lambda}, which can then be used in the phylogenetic transformation.

Availability: PCCA is distributed as DOS/Windows, Mac OS X and Linux/Unix executables with a detailed program manual and is freely available on the World Wide Web at:

http://anolis.oeb.harvard.edu/~liam/programs/.

Contact: lrevell{at}fas.harvard.edu

Associate Editor: Keith Crandall

Received on November 14, 2007; revised on January 7, 2008; accepted on February 15, 2008

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