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

Jean Philippe Fortin; Timothy J. Triche; Kasper D. Hansen

doi:10.1093/bioinformatics/btw691

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

Jean Philippe Fortin, Timothy J. Triche, Kasper D. Hansen

Bloomberg School of Public Health

Research output: Contribution to journal › Article › peer-review

181 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	558-560
Number of pages	3
Journal	Bioinformatics
Volume	33
Issue number	4
DOIs	https://doi.org/10.1093/bioinformatics/btw691
State	Published - Feb 15 2017

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

Access to Document

10.1093/bioinformatics/btw691

Cite this

@article{1b923670f4a24449aa66c347f71dc43c,

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

abstract = "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.",

author = "Fortin, {Jean Philippe} and Triche, {Timothy J.} and Hansen, {Kasper D.}",

note = "Funding Information: Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award number U24CA180996. Dr. Triche gratefully acknowledges support from the Leukemia & Lymphoma Society Quest for Cures program, the Tower Cancer Research Foundation, the St. Baldrick{\textquoteright}s Foundation Pathway Directed Treatment for Refractory AML Consortium grant and the Jane Anne Nohl Hematology Research Support Fund. Publisher Copyright: {\textcopyright} 2017 The Author.",

year = "2017",

month = feb,

day = "15",

doi = "10.1093/bioinformatics/btw691",

language = "English (US)",

volume = "33",

pages = "558--560",

journal = "Bioinformatics",

issn = "1367-4803",

publisher = "Oxford University Press",

number = "4",

}

TY - JOUR

T1 - Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi

AU - Fortin, Jean Philippe

AU - Triche, Timothy J.

AU - Hansen, Kasper D.

N1 - Funding Information: Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award number U24CA180996. Dr. Triche gratefully acknowledges support from the Leukemia & Lymphoma Society Quest for Cures program, the Tower Cancer Research Foundation, the St. Baldrick’s Foundation Pathway Directed Treatment for Refractory AML Consortium grant and the Jane Anne Nohl Hematology Research Support Fund. Publisher Copyright: © 2017 The Author.

PY - 2017/2/15

Y1 - 2017/2/15

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85016984334&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85016984334&partnerID=8YFLogxK

U2 - 10.1093/bioinformatics/btw691

DO - 10.1093/bioinformatics/btw691

M3 - Article

C2 - 28035024

AN - SCOPUS:85016984334

SN - 1367-4803

VL - 33

SP - 558

EP - 560

JO - Bioinformatics

JF - Bioinformatics

IS - 4

ER -

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

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this