Visualization and Statistical Comparisons of Microbial Communities Using R Packages on Phylochip Data


S. Holmes1, A. Alekseyenko2, A. Timme1, T. Nelson3, P.J. Pasricha4, A. Spormann3



1Statistics Department, Stanford University, Stanford, CA 94305, USA;
2Center for Health Informatics and Bioinformatics, NYU School of Medicine, New York, NY USA;
3Department of Civil and Environmental Engineering Stanford University, Clark Center E-250 318 Campus Drive, Stanford CA, 94305, USA;
4Division of Gastroenterology and Hepatology Stanford University Medical Center Alway Building, Room M211 300 Pasteur Drive, Stanford, CA 94305, USA;

Email: susan@stat.stanford.edu

Pacific Symposium on Biocomputing 16:142-153(2011)


Abstract

This article explains the statistical and computational methodology used to analyze species abundances collected using the LNBL Phylochip in a study of Irritable Bowel Syndrome (IBS) in rats. Some tools already available for the analysis of ordinary microarray data are useful in this type of statistical analysis. For instance in correcting for multiple testing we use Family Wise Error rate control and step-down tests (available in the multtest package). Once the most signi cant species are chosen we use the hypergeometric tests familiar for testing GO categories to test speci c phyla and families. We provide examples of normalization, multivariate projections, batch e ect detection and integration of phylogenetic covariation, as well as tree equalization and robusti cation methods.


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