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Proceedings Paper

Statistical approaches to analyzing multichip data
Author(s): James Roy Johnson; Patrick Hurban; Jeff Woessner; Craig M. Liddell
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Paper Abstract

Processing large quantities of micro-arrays designed for high-throughput gene expression profiling presents a completely new set of challenges that must be addressed if biologically meaningful data are to be generated that can undergo statistical analysis. Sources of variation fall naturally into two classes: instrument and biological variation. Each source of variation must be adequately addressed by controlling systematic instrument and operation error, building empirically derived error models, and adequately characterizing the variability observed in biological controls. Finally, the tools used to derive biological meaning from gene expression profiling data must closely tie to the error models and the processes used to generate these data. Robust statistical techniques are appropriate methods for analysis of gene expression profiling data derived from micro-arrays, where adequate characterization of the sources of variation are quantified. No matter how complex or powerful the analysis tools may be, if they are not designed and utilized in this context then the results may remain questionable. At Paradigm Genetics the implementation of these techniques within the gene expression profile platform with the mustard plant, Arabidopsis thaliana, are providing a basis for integrated analysis of micro-array observed data.

Paper Details

Date Published: 4 June 2001
PDF: 8 pages
Proc. SPIE 4266, Microarrays: Optical Technologies and Informatics, (4 June 2001); doi: 10.1117/12.427988
Show Author Affiliations
James Roy Johnson, Paradigm Genetics, Inc. (United States)
Patrick Hurban, Paradigm Genetics, Inc. (United States)
Jeff Woessner, Paradigm Genetics, Inc. (United States)
Craig M. Liddell, Paradigm Genetics, Inc. (United States)


Published in SPIE Proceedings Vol. 4266:
Microarrays: Optical Technologies and Informatics
Michael L. Bittner; Yidong Chen; Andreas N. Dorsel; Edward R. Dougherty, Editor(s)

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