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

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 Hu...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Bioinformatics (Oxford, England) Ročník 33; číslo 4; s. 558 - 560
Hlavní autori: Fortin, Jean-Philippe, Triche, Timothy J., Hansen, Kasper D
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England Oxford University Press 15.02.2017
Predmet:
Applications Notes
DNA Methylation
Epigenomics - methods
Humans
Oligonucleotide Array Sequence Analysis - methods
Sequence Analysis, DNA - methods
Software
ISSN:1367-4803, 1367-4811, 1367-4811
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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. The minfi package version 1.19.12 or higher is available for all platforms from the Bioconductor project. khansen@jhsph.edu. Supplementary data are available at Bioinformatics online.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1367-4803
1367-4811
1367-4811
DOI:10.1093/bioinformatics/btw691