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Functional normalization of 450k methylation array data improves replication in large cancer studies

Open access
Fortin, Jean-Philippe, Labbe, Aurélie, Lemire, Mathieu, Zanke, Brent W, Hudson, Thomas J, Fertig, Elana J, Greenwood, Celia MT, Hansen, Kasper D·2014·Genome Biology

Abstract

We propose an extension to quantile normalization that removes unwanted technical variation using control probes. We adapt our algorithm, functional normalization, to the Illumina 450k methylation array and address the open problem of normalizing methylation data with global epigenetic changes, such as human cancers. Using data sets from The Cancer Genome Atlas and a large case–control study, we show that our algorithm outperforms all existing normalization methods with respect to replication of results between experiments, and yields robust results even in the presence of batch effects. Functional normalization can be applied to any microarray platform, provided suitable control probes are available.

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Metadata

Authors
Fortin, J.-P., Labbe, A., Lemire, M., Zanke, B. W., Hudson, T. J., Fertig, E. J., Greenwood, C. M., & Hansen, K. D.
Venue
Genome Biology
Published
2014-12-03
Volume
15
Issue
11
Pages
503-503
ISSN
  • 1465-6906 (ISSN-L)
  • 1474-760X
OpenAlex
W2129915465
Cited by
892
References
56
FWCI
14.60
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Functional normalization of 450k methylation array data improves replication in large cancer studies. https://app.cochat.ai/papers/10.1186/s13059-014-0503-2
The paper
Fortin, J.-P., Labbe, A., Lemire, M., Zanke, B. W., Hudson, T. J., Fertig, E. J., Greenwood, C. M., & Hansen, K. D. (2014). Functional normalization of 450k methylation array data improves replication in large cancer studies. Genome Biology. https://doi.org/10.1186/s13059-014-0503-2

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