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Publication Date:
October 2010
ISSN:
1544-6115
DOI:
10.2202/1544-6115.1590

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Editor-in-Chief: Stumpf, Michael P.H.

Editorial Board Member: Beaumont, Mark / Binder, Harald / Gupta, Mayetri / Hubbard, Alan E. / Husmeier, Dirk / Ji, Hongkai / Keles, Sunduz / Kerr, Kathleen / Lazzeroni, Laura / Lin, Shili / Ma, Ping / Marjoram, Paul / Mertens, Bart / Nerman, Olle / G. Petretto, Enrico / Plagnol, Vincent / Purdom, Elizabeth / Robin, Stéphane / Rzhetsky, Andrey / Sanguinetti, Guido / van der Laan, Mark J. / von Haeseler, Arndt / Weeks, Daniel E. / Wiuf, Carsten / Zhao, Hongyu

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Rank 27 out of 116 in category Statistics & Probability in the 2011 Thomson Reuters Journal Citation Report/Science Edition

The Detection of Blur in Affymetrix GeneChips

Graham J. G. Upton / Andrew P Harrison

1University of Essex

1University of Essex

Citation Information: Statistical Applications in Genetics and Molecular Biology. Volume 9, Issue 1, Pages –, ISSN (Online) 1544-6115, DOI: 10.2202/1544-6115.1590, October 2010

Publication History:
Published Online:
2010-10-18

High correlations were obtained between probes in seemingly unrelated probe sets, following an examination of the data from thousands of Affymetrix GeneChips. Investigation revealed that these unexpected correlations were between probes that were adjacent to high-valued probes. Using carefully selected probes, together with simple linear models, the extent of blur has been measured for each CEL file. The cause is shown to be attributable to poorly performing scanners. Blur can result in the doubling of the values of thousands of probes. This in turn can lead to the doubling of the expression level for hundreds of probe sets.

Keywords: microarray; correlation; blur; scanner

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