Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi | Zendy

Jean-Philippe Fortin | Zendy; Timothy J. Triche | Zendy; Kasper D. Hansen | Zendy

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Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi

Author(s) -

Jean-Philippe Fortin,

Timothy J. Triche,

Kasper D. Hansen

Publication year - 2016

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btw691

Subject(s) - bioconductor , normalization (sociology) , preprocessor , computer science , epic , dna methylation , data mining , r package , computational biology , biology , artificial intelligence , genetics , gene , computational science , art , gene expression , literature , sociology , anthropology

The minfi package is widely used for analyzing Illumina DNA methylation array data. Here we describe modifications to the minfi package required to support the HumanMethylationEPIC ('EPIC') array from Illumina. We discuss methods for the joint analysis and normalization of data from the HumanMethylation450 ('450k') and EPIC platforms. We introduce the single-sample Noob ( ssNoob ) method, a normalization procedure suitable for incremental preprocessing of individual methylation arrays and conclude that this method should be used when integrating data from multiple generations of Infinium methylation arrays. We show how to use reference 450k datasets to estimate cell type composition of samples on EPIC arrays. The cumulative effect of these updates is to ensure that minfi provides the tools to best integrate existing and forthcoming Illumina methylation array data.

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