IMAGE: high-powered detection of genetic effects on DNA methylation using integrated methylation QTL mapping and allele-specific analysis.

Autor: Fan Y; Systems Engineering Institute, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, People's Republic of China.; Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA., Vilgalys TP; Departments of Evolutionary Anthropology and Biology, Duke University, Durham, NC, 27708, USA., Sun S; Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA., Peng Q; Systems Engineering Institute, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, People's Republic of China., Tung J; Departments of Evolutionary Anthropology and Biology, Duke University, Durham, NC, 27708, USA.; Duke University Population Research Institute, Duke University, Durham, NC, 27708, USA., Zhou X; Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA. xzhousph@umich.edu.; Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, 48109, USA. xzhousph@umich.edu.
Jazyk: angličtina
Zdroj: Genome biology [Genome Biol] 2019 Oct 24; Vol. 20 (1), pp. 220. Date of Electronic Publication: 2019 Oct 24.
DOI: 10.1186/s13059-019-1813-1
Abstrakt: Identifying genetic variants that are associated with methylation variation-an analysis commonly referred to as methylation quantitative trait locus (mQTL) mapping-is important for understanding the epigenetic mechanisms underlying genotype-trait associations. Here, we develop a statistical method, IMAGE, for mQTL mapping in sequencing-based methylation studies. IMAGE properly accounts for the count nature of bisulfite sequencing data and incorporates allele-specific methylation patterns from heterozygous individuals to enable more powerful mQTL discovery. We compare IMAGE with existing approaches through extensive simulation. We also apply IMAGE to analyze two bisulfite sequencing studies, in which IMAGE identifies more mQTL than existing approaches.
Databáze: MEDLINE
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