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Bioinformatics. 2017 Feb 15;33(4):558-560. doi: 10.1093/bioinformatics/btw691.

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

Author information

1
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
2
Jane Anne Nohl Division of Hematology, Keck School of Medicine of USC, Los Angeles, CA 90033, USA.
3
McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.

Abstract

Summary:

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.

Availability and Implementation:

The minfi package version 1.19.12 or higher is available for all platforms from the Bioconductor project.

Contact:

khansen@jhsph.edu.

Supplementary information:

Supplementary data are available at Bioinformatics online.

PMID:
28035024
PMCID:
PMC5408810
DOI:
10.1093/bioinformatics/btw691
[Indexed for MEDLINE]
Free PMC Article

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