Methylation-eQTL analysis in cancer research | Zendy

Yusha Liu | Zendy; Keith Baggerly | Zendy; Elias Orouji | Zendy; Ganiraju C. Manyam | Zendy; Huiqin Chen | Zendy; Michael Lam | Zendy; Jennifer S. Davis | Zendy; Michael S. Lee | Zendy; Bradley M. Broom | Zendy; David G. Menter | Zendy; Kunal Rai | Zendy; Scott Kopetz | Zendy; Jeffrey S. Morris | Zendy

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Methylation-eQTL analysis in cancer research

Author(s) -

Yusha Liu,

Keith Baggerly,

Elias Orouji,

Ganiraju C. Manyam,

Huiqin Chen,

Michael Lam,

Jennifer S. Davis,

Michael S. Lee,

Bradley M. Broom,

David G. Menter,

Kunal Rai,

Scott Kopetz,

Jeffrey S. Morris

Publication year - 2021

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab443

Subject(s) - expression quantitative trait loci , dna methylation , methylation , epigenetics , biology , epigenomics , computational biology , gene , genetics , gene expression , regulation of gene expression , genotype , single nucleotide polymorphism

DNA methylation is a key epigenetic factor regulating gene expression. While promoter methylation has been well studied, recent publications have revealed that functionally important methylation also occurs in intergenic and distal regions, and varies across genes and tissue types. Given the growing importance of inter-platform integrative genomic analyses, there is an urgent need to develop methods to discover and characterize gene-level relationships between methylation and expression.

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