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Bioinformatics Advance Access published online on February 25, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti343
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received January 14, 2005
Revised February 15, 2005
Accepted February 17, 2005

Applications note

A web-based tool for principal component and significance analysis of microarray data

Alexei A. Sharov 1, Dawood B. Dudekula 1, and Minoru S. H. Ko 1*

1 Developmental Genomics and Aging Section, Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA

* To whom correspondence should be addressed.
Minoru S. H. Ko, E-mail: kom{at}mail.nih.gov


  Abstract

Summary: We have developed a program for microarray data analysis, which features the False Discovery Rate (FDR) for testing statistical significance and the Principal Component Analysis (PCA) using the Singular Value Decomposition (SVD) method for detecting the global trends of gene expression patterns. Additional features include analysis of variance (ANOVA) with multiple methods for error variance adjustment, correction of cross-channel correlation for two-color microarrays, identification of genes specific to each cluster of tissue samples, biplot of tissues and corresponding tissue-specific genes, clustering of genes that are correlated with each principal component (PC), 3-dimensional graphics based on virtual reality modeling language (VRML), and sharing of PC between different experiments. The software also supports parameter adjustment, gene search, and graphical output of results. The software is implemented as a web tool, and thus the speed of analysis does not depend on the power of a client computer.

Availability: The tool can be used on-line or downloaded at http://lgsun.grc.nia.nih.gov/ANOVA/.


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