A gene expression bar code for microarray data

Michael J. Zilliox; Rafael A. Irizarry

doi:10.1038/nmeth1102

A gene expression bar code for microarray data

Michael J. Zilliox, Rafael A. Irizarry

Research output: Contribution to journal › Article › peer-review

98 Scopus citations

Abstract

The ability to measure genome-wide expression holds great promise for characterizing cells and distinguishing diseased from normal tissues. Thus far, microarray technology has been useful only for measuring relative expression between two or more samples, which has handicapped its ability to classify tissue types. Here we present a method that can successfully predict tissue type based on data from a single hybridization. A preliminary web-tool is available online (http://rafalab.jhsph.edu/barcode/).

Original language	English (US)
Pages (from-to)	911-913
Number of pages	3
Journal	Nature Methods
Volume	4
Issue number	11
DOIs	https://doi.org/10.1038/nmeth1102
State	Published - Nov 2007
Externally published	Yes

ASJC Scopus subject areas

Biotechnology
Biochemistry
Molecular Biology
Cell Biology

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10.1038/nmeth1102

Cite this

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abstract = "The ability to measure genome-wide expression holds great promise for characterizing cells and distinguishing diseased from normal tissues. Thus far, microarray technology has been useful only for measuring relative expression between two or more samples, which has handicapped its ability to classify tissue types. Here we present a method that can successfully predict tissue type based on data from a single hybridization. A preliminary web-tool is available online (http://rafalab.jhsph.edu/barcode/).",

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A gene expression bar code for microarray data

Abstract

ASJC Scopus subject areas

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