TY  - JOUR
AU  - Perrier, Flavie
AU  - Novoloaca, Alexei
AU  - Ambatipudi, Srikant
AU  - Baglietto, Laura
AU  - Ghantous, Akram
AU  - Perduca, Vittorio
AU  - Barrdahl, Myrto
AU  - Harlid, Sophia
AU  - Ong, Ken K
AU  - Cardona, Alexia
AU  - Polidoro, Silvia
AU  - Nøst, Therese Haugdahl
AU  - Overvad, Kim
AU  - Omichessan, Hanane
AU  - Dollé, Martijn
AU  - Bamia, Christina
AU  - Huerta, José Marìa
AU  - Vineis, Paolo
AU  - Herceg, Zdenko
AU  - Romieu, Isabelle
AU  - Ferrari, Pietro
TI  - Identifying and correcting epigenetics measurements for systematic sources of variation.
JO  - Clinical epigenetics
VL  - 10
IS  - 1
SN  - 1868-7083
CY  - [S.l.]
PB  - BioMed Central
M1  - DKFZ-2018-00404
SP  - 38
PY  - 2018
AB  - 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.A sizeable proportion of systematic variability due to variables expressing 'batch' and 'sample position' within 'chip' was identified, with values of the partial R2 statistics equal to 9.5 and 11.4
LB  - PUB:(DE-HGF)16
C6  - pmid:29588806
C2  - pmc:PMC5863487
DO  - DOI:10.1186/s13148-018-0471-6
UR  - https://inrepo02.dkfz.de/record/132751
ER  -