Abstract #302363

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JSM 2003 Abstract #302363
Activity Number: 64
Type: Invited
Date/Time: Sunday, August 3, 2003 : 6:00 PM to 8:00 PM
Sponsor: Section on Statistical Computing
Abstract - #302363
Title: The Bioconductor Project: Open-source Statistical Software for the Analysis of Genomic Data
Author(s): Sandrine Dudoit*+
Companies: University of California, Berkeley
Address: Division of Biostatistics, Berkeley, CA, 94720-7360,
Keywords:
Abstract:

DNA microarrays are high-throughput biological assays that can be used to measure expression levels in cells for entire genomes. Microarray experiments are being performed increasingly in biological and medical research to address a wide range of problems. In cancer research, microarrays are used to study the molecular variations among tumors with the aim of developing better diagnosis and treatment strategies for the disease. Microarray experiments generate large and complex multivariate datasets. The application of sound statistical design and analysis principles can greatly improve the efficiency and reliability of these experiments throughout the data acquisition and analysis process. Efficient and well-designed statistical software is an essential catalyst between the development of statistical methodology and its positive and timely impact on biology. We will present a survey of statistical methods and software for the analysis of DNA microarray data. Specifically, we will discuss computing resources developed as part of the Bioconductor project. This collaborative effort aims to produce an open source and open development computing environment for the analysis of genomic data (www.bioconductor.org).

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