Back to Search Start Over

Modeling dependency structures in 450k DNA methylation data

Authors :
Miina Ollikainen
Kristina Gervin
Emma Cazaly
Robert Lyle
Haakon E. Nustad
Yuval Benjamini
Ingelin Steinsland
Jaakko Kaprio
Helsinki Institute of Life Science HiLIFE, Joint Activities
Institute for Molecular Medicine Finland
Source :
Bioinformatics
Publication Year :
2021
Publisher :
Oxford University Press (OUP), 2021.

Abstract

Motivation DNA methylation has been shown to be spatially dependent across chromosomes. Previous studies have focused on the influence of genomic context on the dependency structure, while not considering differences in dependency structure between individuals. Results We modeled spatial dependency with a flexible framework to quantify the dependency structure, focusing on inter-individual differences by exploring the association between dependency parameters and technical and biological variables. The model was applied to a subset of the Finnish Twin Cohort study (N = 1611 individuals). The estimates of the dependency parameters varied considerably across individuals, but were generally consistent across chromosomes within individuals. The variation in dependency parameters was associated with bisulfite conversion plate, zygosity, sex and age. The age differences presumably reflect accumulated environmental exposures and/or accumulated small methylation differences caused by stochastic mitotic events, establishing recognizable, individual patterns more strongly seen in older individuals. Availability and implementation The twin dataset used in the current study are located in the Biobank of the National Institute for Health and Welfare, Finland. All the biobanked data are publicly available for use by qualified researchers following a standardized application procedure (https://thl.fi/en/web/thl-biobank/for-researchers). A R-script for fitting the dependency structure to publicly available DNA methylation data with the software used in this article is provided in supplementary data. Supplementary information Supplementary data are available at Bioinformatics online.

Details

ISSN :
13674811 and 13674803
Volume :
38
Database :
OpenAIRE
Journal :
Bioinformatics
Accession number :
edsair.doi.dedup.....83390e836c7a33f7b8b542a8bdd40ed6