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    Identifying and correcting epigenetics measurements for systematic sources of variation.

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    Authors
    Perrier, Flavie
    Novoloaca, Alexei
    Ambatipudi, Srikant
    Baglietto, Laura
    Ghantous, Akram
    Perduca, Vittorio
    Barrdahl, Myrto
    Harlid, Sophia
    Ong, Ken K
    Cardona, Alexia
    Polidoro, Silvia
    Nøst, Therese Haugdahl
    Overvad, Kim
    Omichessan, Hanane
    Dollé, Martijn
    Bamia, Christina
    Huerta, José Marìa
    Vineis, Paolo
    Herceg, Zdenko
    Romieu, Isabelle
    Ferrari, Pietro
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    Type
    Article
    Language
    en
    
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    Title
    Identifying and correcting epigenetics measurements for systematic sources of variation.
    Published in
    Clin Epigenetics 2018; 10:38
    Publiekssamenvatting
    Methylation measures quantified by microarray techniques can be affected by systematic variation due to the technical processing of samples, which may compromise the accuracy of the measurement process and contribute to bias the estimate of the association under investigation. The quantification of the contribution of the systematic source of variation is challenging in datasets characterized by hundreds of thousands of features.In this study, we introduce a method previously developed for the analysis of metabolomics data to evaluate the performance of existing normalizing techniques to correct for unwanted variation. Illumina Infinium HumanMethylation450K was used to acquire methylation levels in over 421,000 CpG sites for 902 study participants of a case-control study on breast cancer nested within the EPIC cohort. The principal component partial R-square (PC-PR2) analysis was used to identify and quantify the variability attributable to potential systematic sources of variation. Three correcting techniques, namely ComBat, surrogate variables analysis (SVA) and a linear regression model to compute residuals were applied. The impact of each correcting method on the association between smoking status and DNA methylation levels was evaluated, and results were compared with findings from a large meta-analysis.
    DOI
    10.1186/s13148-018-0471-6
    PMID
    29588806
    URI
    http://hdl.handle.net/10029/621807
    ae974a485f413a2113503eed53cd6c53
    10.1186/s13148-018-0471-6
    Scopus Count
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