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

dc.contributor.authorFan, Yue
dc.contributor.authorVilgalys, Tauras P
dc.contributor.authorSun, Shiquan
dc.contributor.authorPeng, Qinke
dc.contributor.authorTung, Jenny
dc.contributor.authorZhou, Xiang
dc.date.accessioned2019-11-26T13:52:51Z
dc.date.available2019-11-26T13:52:51Z
dc.date.issued2019-10-24
dc.identifier.citationGenome Biology. 2019 Oct 24;20(1):220
dc.identifier.urihttps://doi.org/10.1186/s13059-019-1813-1
dc.identifier.urihttps://hdl.handle.net/2027.42/152238
dc.description.abstractAbstract 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.
dc.titleIMAGE: high-powered detection of genetic effects on DNA methylation using integrated methylation QTL mapping and allele-specific analysis
dc.typeArticleen_US
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/152238/1/13059_2019_Article_1813.pdf
dc.language.rfc3066en
dc.rights.holderThe Author(s).
dc.date.updated2019-11-26T13:52:53Z
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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