Abstract: The Remote Analysis Computation for gene Expression data (RACE) suite, which is a new open-source web-tool for the analysis of DNA microarray data, will be presented. RACE performs probe level data preprocessing, extensive quality checks, data visualization, 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 gene, and provides a Gene Ontology-term analysis tool 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.

Short Bio: Beate Sick received her Ph.D. degree in Physical Chemstry as well as her postgraduate degree in Applied Statistics from the Eidgenoessische Technische Hochschule (ETH) Zurich, Switzerland, in 2000. After postdoctoral work on the visualization of protein function and dynamics she changed to a diagnostics startup company where she was responsible for protein expression analysis. Since 2003 she has been leading the bioinformatics unit of the DNA array facility at the University of Lausanne, Switzerland.