A systematic study of normalization methods for Infinium 450K methylation data using whole-genome bisulfite sequencing data

DNA methylation plays an important role in disease etiology. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a widely used platform in large-scale epidemiologic studies. This platform can efficiently and simultaneously measure methylation levels at ∼480,000 CpG sites in the human genome...

Full description

Saved in:
Bibliographic Details
Published in:Epigenetics 2015-07, Vol.10 (7), p.662-669
Main Authors: Wang, Ting, Guan, Weihua, Lin, Jerome, Boutaoui, Nadia, Canino, Glorisa, Luo, Jianhua, Celedón, Juan Carlos, Chen, Wei
Format: Article
Language:English
Subjects:
CpG Islands
DNA Methylation
epigenetics
Genome, Human
Genome-Wide Association Study
High-Throughput Nucleotide Sequencing - methods
Humans
Illumina 450K
Leukocytes - metabolism
Mathematical Concepts
microarray
normalization
Research Paper
Sulfites - chemistry
whole-genome bisulfite sequencing (WGBS)
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:DNA methylation plays an important role in disease etiology. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a widely used platform in large-scale epidemiologic studies. This platform can efficiently and simultaneously measure methylation levels at ∼480,000 CpG sites in the human genome in multiple study samples. Due to the intrinsic chip design of 2 types of chemistry probes, data normalization or preprocessing is a critical step to consider before data analysis. To date, numerous methods and pipelines have been developed for this purpose, and some studies have been conducted to evaluate different methods. However, validation studies have often been limited to a small number of CpG sites to reduce the variability in technical replicates. In this study, we measured methylation on a set of samples using both whole-genome bisulfite sequencing (WGBS) and 450K chips. We used WGBS data as a gold standard of true methylation states in cells to compare the performances of 8 normalization methods for 450K data on a genome-wide scale. Analyses on our dataset indicate that the most effective methods are peak-based correction (PBC) and quantile normalization plus β-mixture quantile normalization (QN.BMIQ). To our knowledge, this is the first study to systematically compare existing normalization methods for Illumina 450K data using novel WGBS data. Our results provide a benchmark reference for the analysis of DNA methylation chip data, particularly in white blood cells.
ISSN:1559-2294
1559-2308
DOI:10.1080/15592294.2015.1057384