title: DIVAN: accurate identification of non-coding disease-specific risk variants using multi-omics profiles.
abstract: Understanding the link between non-coding sequence variants, identified in genome-wide association studies, and the pathophysiology of complex diseases remains challenging due to a lack of annotations in non-coding regions. To overcome this, we developed DIVAN, a novel feature selection and ensemble learning framework, which identifies disease-specific risk variants by leveraging a comprehensive collection of genome-wide epigenomic profiles across cell types and factors, along with other static genomic features. DIVAN accurately and robustly recognizes non-coding disease-specific risk variants under multiple testing scenarios; among all the features, histone marks, especially those marks associated with repressed chromatin, are often more informative than others.
authors.affiliation: Department of Mathematics and Computer Science, Emory University, Atlanta, GA, 30322, USA.
authors.forename: Li
authors.initials: L
authors.lastname: Chen
authors.affiliation: Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
authors.forename: Peng
authors.initials: P
authors.lastname: Jin
authors.affiliation: Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA. zhaohui.qin@emory.edu.|Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, 30322, USA. zhaohui.qin@emory.edu.
authors.forename: Zhaohui S
authors.initials: ZS
authors.lastname: Qin
mesh_terms: D002843:Chromatin / Q000235:genetics; D019295:Computational Biology / Q000379:methods; D004194:Disease / Q000235:genetics*; D057890:Epigenomics; D014644:Genetic Variation; D015894:Genome, Human; D055106:Genome-Wide Association Study; D042421:Histone Code / Q000235:genetics; D006657:Histones / Q000235:genetics; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D012307:Risk Factors
chemical_list: D002843:Chromatin; D006657:Histones
keywords: Disease-specific; Ensemble learning; Epigenomics; Feature selection; Histone marks; Non-coding variants; Variant annotation