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Bioinformatics and Computational Biology Solutions Using R and BioconductorPreprocessing High-density Oligonucleotide Arrays

Bioinformatics and Computational Biology Solutions Using R and Bioconductor: Preprocessing... [High-density oligonucleotide expression arrays are a widely used microarray platform. Affymetrix GeneChip arrays dominate this market. An important distinction between the GeneChip and other technologies is that on GeneChips, multiple short probes are used to measure gene expression levels. This makes preprocessing particularly important when using this platform. This chapter begins by describing how to import probe-level data into the system and how these data can be examined using the facilities of the AffyBatch class. Then we will describe background adjustment, normalization, and summarization methods. Functionality for GeneChip probe-level data is provided by the affy, affyPLM, affycomp, gcrma, and affypdnn packages. All these tools are useful for preprocessing probe-level data stored in an AffyBatch object into expression-level data stored in an exprSet object. Because there are many competing methods for this preprocessing step, it is useful to have a way to assess the differences. In Bioconductor, this can be carried out using the affycomp package, which we discuss briefly.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Bioinformatics and Computational Biology Solutions Using R and BioconductorPreprocessing High-density Oligonucleotide Arrays

Part of the Statistics for Biology and Health Book Series
Editors: Gentleman, Robert; Carey, Vincent J.; Huber, Wolfgang; Irizarry, Rafael A.; Dudoit, Sandrine

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Publisher
Springer New York
Copyright
© Springer Science+Business Media, Inc. 2005
ISBN
978-0-387-25146-2
Pages
13 –32
DOI
10.1007/0-387-29362-0_2
Publisher site
See Chapter on Publisher Site

Abstract

[High-density oligonucleotide expression arrays are a widely used microarray platform. Affymetrix GeneChip arrays dominate this market. An important distinction between the GeneChip and other technologies is that on GeneChips, multiple short probes are used to measure gene expression levels. This makes preprocessing particularly important when using this platform. This chapter begins by describing how to import probe-level data into the system and how these data can be examined using the facilities of the AffyBatch class. Then we will describe background adjustment, normalization, and summarization methods. Functionality for GeneChip probe-level data is provided by the affy, affyPLM, affycomp, gcrma, and affypdnn packages. All these tools are useful for preprocessing probe-level data stored in an AffyBatch object into expression-level data stored in an exprSet object. Because there are many competing methods for this preprocessing step, it is useful to have a way to assess the differences. In Bioconductor, this can be carried out using the affycomp package, which we discuss briefly.]

Published: Jan 1, 2005

Keywords: Perfect Match; Background Correction; Probe Intensity; Expression Measure; Quantile Normalization

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