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

被引：580

作者：

Fortin, Jean-Philippe ^{[1
]}

Labbe, Aurelie ^{[2
,3
,4
]}

Lemire, Mathieu ^{[5
]}

Zanke, Brent W. ^{[6
]}

Hudson, Thomas J. ^{[5
,7
,8
]}

Fertig, Elana J. ^{[9
]}

Greenwood, Celia M. T. ^{[2
,10
,11
]}

Hansen, Kasper D. apy ^{[1
,12
]}

机构：

[1] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Biostat, Baltimore, MD 21205 USA

[2] McGill Univ, Dept Epidemiol Biostat & Occupat Hlth, Montreal, PQ H3A 1A2, Canada

[3] McGill Univ, Douglas Mental Hlth Univ Inst, Verdun, PQ H4H 1R3, Canada

[4] McGill Univ, Dept Psychiat, Montreal, PQ H3A 1A1, Canada

[5] Ontario Inst Canc Res, Toronto, ON M5G 0A3, Canada

[6] Ottawa Hosp Res Inst, Clin Epidemiol Program, Ottawa, ON K1Y 4E9, Canada

[7] Univ Toronto, Dept Mol Genet, Toronto, ON M5G 1L7, Canada

[8] Univ Toronto, Dept Med Biophys, Toronto, ON M5G 1L7, Canada

[9] Johns Hopkins Univ, Sidney Kimmel Comprehens Canc Ctr, Dept Oncol, Baltimore, MD 21205 USA

[10] Jewish Gen Hosp Montreal, Lady Davis Inst Med Res, Montreal, PQ H3T 1E2, Canada

[11] McGill Univ, Dept Oncol, Montreal, PQ H2W 1S6, Canada

[12] Johns Hopkins Sch Med, McKusick Nathans Inst Genet Med, Baltimore, MD 21287 USA

来源：

GENOME BIOLOGY | 2014年 / 15卷 / 12期

基金：

美国国家卫生研究院; 加拿大自然科学与工程研究理事会;

关键词：

EPIGENOME-WIDE ASSOCIATION; DNA METHYLATION; CELLULAR HETEROGENEITY; QUANTILE NORMALIZATION; UNWANTED VARIATION; SUBSET-QUANTILE; GENE-EXPRESSION; HYPOMETHYLATION; BIOCONDUCTOR; SUMMARIES;

D O I：

10.1186/s13059-014-0503-2

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 [微生物学]; 090105 [作物生产系统与生态工程];

摘要：

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.

引用

页数：17

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