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Functional normalization of 450k methylation array data improves replication in large cancer studies
Jean-Philippe Fortin, Aurélie Labbe, Mathieu Lemire, Brent W. Zanke, View ORCID ProfileThomas J. Hudson, Elana J. Fertig, Celia M.T. Greenwood, View ORCID ProfileKasper D. Hansen
doi: https://doi.org/10.1101/002956
Jean-Philippe Fortin
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
Aurélie Labbe
2Department of Epidemiology, Biostatistics and Occupational Health, McGill University
3Douglas Mental Health University Institute, McGill University
Mathieu Lemire
4Ontario Institute of Cancer Research
Brent W. Zanke
5Clinical Epidemiology Program, Ottawa Hospital Research Institute
Thomas J. Hudson
4Ontario Institute of Cancer Research
6Departments of Molecular Genetics and Medical Biophysics, University of Toronto
Elana J. Fertig
7Department of Oncology, Sidney Kimmel Cancer Center, Johns Hopkins School of Medicine
Celia M.T. Greenwood
2Department of Epidemiology, Biostatistics and Occupational Health, McGill University
8Lady Davis Institute for Medical Research, Jewish General Hospital Montreal
9Department of Oncology, McGill University
Kasper D. Hansen
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
10McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine

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Posted February 23, 2014.
Functional normalization of 450k methylation array data improves replication in large cancer studies
Jean-Philippe Fortin, Aurélie Labbe, Mathieu Lemire, Brent W. Zanke, Thomas J. Hudson, Elana J. Fertig, Celia M.T. Greenwood, Kasper D. Hansen
bioRxiv 002956; doi: https://doi.org/10.1101/002956
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