W638–W643 Nucleic Acids Research, 2005, Vol. 33, Web Server issue doi:10.1093/nar/gki490 RACE: Remote Analysis Computation for gene Expression data Michael Psarros, Steffen Heber1, Manuela Sick, Gnanasekaran Thoppae, Keith Harshman and Beate Sick* DNA Array Facility, Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland and 1Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA Received February 14, 2005; Revised April 12, 2005; Accepted April 25, 2005 ABSTRACT The Remote Analysis Computation for gene Expression data (RACE) suite is a collection of bioin- formatics web tools designed for the analysis of DNA microarray data. RACE performs probe-level data pre- processing, extensive quality checks, data visualiza- tion and data normalization for Affymetrix GeneChips. In addition, it offers differential expression analysis on normalized expression levels from any array platform. RACE estimates the false discovery rates of lists of potentially regulated genes and provides a Gene Ontology-term analysis tool for GeneChip data to support the biological interpretation and annotation of results. The analysis is fully automated but can be customized by flexible parameter settings. To offer a convenient starting point for subsequent analyses, and to provide maximum transparency, the R scripts used to generate the results can be downloaded along with the output files. RACE is freely available for use at http://race.unil.ch. INTRODUCTION DNA microarrays are standard tools in biology and medicine. An increasingly long list of applications includes the identi- ﬁcation of gene expression changes associated with changes in cell state (1,2), classifying clinical samples based on the under- lying pathological characteristics (3,4), drug development (5) and the functional annotation of genes (6). A typical micro- array experiment might measure expression levels of tens of thousands of genes, and systematic variations introduced into the datasets (e.g. variations in labeling efﬁciencies or scanner settings) can often obscure the biological variation that is of real interest. Furthermore, once differentially expressed genes have been identiﬁed, inferring function based simply on their expression pattern can be both arduous and ineffective. Hence, bioinformatics tools that facilitate rigorous data analysis and interpretation are of the highest importance. Presented here is Remote Analysis Computation for gene Expression data (RACE), a web server which provides some solutions to these problems. Microarray data analysis typically begins with data quality checks and data normalization (7). Once normalized expres- sion levels are determined, expression ratios can be calculated and differentially expressed genes identiﬁed. At this stage of data analysis, the magnitude and signiﬁcance of gene expres- sion changes as well as the false discovery rate are important measures. Once a list of differentially expressed genes is iden- tiﬁed, the task often turns to describing and interpreting the biological signiﬁcance of the results. An often useful approach is to compile a list of the Gene Ontology (GO) terms associ- ated with the differentially expressed genes (8). This provides an overview of the biological, physiological and cellular pro- cesses potentially involved in the biological phenomena and suggests directions for further studies. A number of very useful web tools for microarray data analysis exist (e.g. 9–13). RACE contributes to the ﬁeld by providing access to a wide range of quality checks, probe-level methods and state-of-the-art normalization techniques for Affymetrix raw data. To the best of our knowledge, these are not provided by any other publicly available server. Addi- tionally, RACE provides tools to identify lists of different- ially expressed genes and to determine and investigate the associated GO-term composition of those genes. To facilitate subsequent analyses and guarantee maximal transparency and reproducibility, the R script used to generate the results is provided. SYSTEM AND MODULE DESIGN RACE is divided into two components: the user interface and the analysis part. RACE uses basic authentication provided by Apache. HTTP communication is exclusively via port 80, making the system easily accessible through a ﬁrewall. *To whom correspondence should be addressed. Tel: +1 41 21 692 3909; Fax: +1 41 21 692 3905; Email: Beate.Sick@unil.ch The Author 2005. Published by Oxford University Press. All rights reserved. The online version of this article has been published under an open access model. 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