Journal Article

Matching methods for observational microarray studies

Ruth Heller, Elisabetta Manduchi and Dylan S. Small

in Bioinformatics

Volume 25, issue 7, pages 904-909
Published in print April 2009 | ISSN: 1367-4803
Published online December 2008 | e-ISSN: 1460-2059 | DOI:
Matching methods for observational microarray studies

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Motivation: We address the problem of identifying differentially expressed genes between two conditions in the scenario where the data arise from an observational study, in which confounding factors are likely to be present.

Results: We suggest to use matching methods to balance two groups of observed cases on measured covariates, and to identify differentially expressed genes using a test suited to matched data. We illustrate this approach on two microarray studies: the first study consists of data from patients with two cancer subtypes, and the second study consists of data from AMKL patients with and without Down syndrome.

Availability: R code ( for implementing our approach is included as Supplementary Material.


Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  5009 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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