Automatic quality assessment of Affymetrix GeneChip data

Computing reliable gene expression levels from microarray experiments is a sophisticated process with many potential pitfalls. Quality control is one of the most important steps in this process. We present a web based expert system for automatic quality assessment of Affymetrix GeneChip data. Our approach combines multiple quality metrics with supervised machine learning in order to identify data of low quality. Our system approximates expert opinion as represented in a knowledge base consisting of 41 microarray experiments with 352 CEL files annotated by a domain expert. GeneChips of low quality are detected automatically and can be excluded from subsequent analysis. This is especially important for large experiments or can assist the inexperienced users. Our expert system is fully implemented and integrated into a publicly available remote analysis computation engine for gene expression data. Categories and Subject Descriptors J.3 [Life and Medical Sciences]: biology and genetics;...

• Type: Conference
• Year: 2006
• Where: ACMSE
• Authors: Steffen Heber, Beate Sick
• Keywords: ACMSE 2006, Affymetrix GeneChip, Low Quality, Quality Assessment, Theoretical Computer Science