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Bioinformatics and Computational Biology Solutions Using R and BioconductorQuality Assessment of Affymetrix GeneChip Data

Bioinformatics and Computational Biology Solutions Using R and Bioconductor: Quality Assessment... [This chapter covers quality assessment for Affymetrix GeneChip data. The focus is on procedures available from the affy and affy-PLM packages. Initially some exploratory plots provided by the affy package, including images of the raw probe-level data, boxplots, histograms, and M vs A plots are examined. Next methods for assessing RNA degradation are discussed, specifically we compare the standard procedures recommended by Affymetrix and RNA degradation plots. Finally, we investigate how appropriate probe-level models yield good quality assessment tools. Chip pseudo-images of residuals and weights obtained from fitting robust linear models to the probe level data can be used as a visual tool for identifying artifacts on GeneChip microarrays. Other output from the probe-level modeling tools provide summary plots that may be used to identify aberrant chips.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Bioinformatics and Computational Biology Solutions Using R and BioconductorQuality Assessment of Affymetrix GeneChip Data

Part of the Statistics for Biology and Health Book Series
Editors: Gentleman, Robert; Carey, Vincent J.; Huber, Wolfgang; Irizarry, Rafael A.; Dudoit, Sandrine
Bolstad, B. M.; Collin, F.; Brettschneider, J.; Simpson, K.; Cope, L.; Irizarry, R. A.; Speed, T.P.
Bioinformatics and Computational Biology Solutions Using R and Bioconductor — Jan 1, 2005
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Publisher
Springer New York
Copyright
© Springer Science+Business Media, Inc. 2005
ISBN
978-0-387-25146-2
Pages
33 –47
DOI
10.1007/0-387-29362-0_3
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter covers quality assessment for Affymetrix GeneChip data. The focus is on procedures available from the affy and affy-PLM packages. Initially some exploratory plots provided by the affy package, including images of the raw probe-level data, boxplots, histograms, and M vs A plots are examined. Next methods for assessing RNA degradation are discussed, specifically we compare the standard procedures recommended by Affymetrix and RNA degradation plots. Finally, we investigate how appropriate probe-level models yield good quality assessment tools. Chip pseudo-images of residuals and weights obtained from fitting robust linear models to the probe level data can be used as a visual tool for identifying artifacts on GeneChip microarrays. Other output from the probe-level modeling tools provide summary plots that may be used to identify aberrant chips.]

Published: Jan 1, 2005

Keywords: Probe Intensity; GeneChip Data; GeneChip Microarrays; Spatial Artifact; Robust Linear Model

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