ArticleIEEE journal of biomedical and health informatics2014
Multiview comodeling to improve subtyping and genetic association of complex diseases.
Article in IEEE journal of biomedical and health informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Cancer classification based on chromatin accessibility profiles with deep adversarial learning model.PLoS computational biology · 2020Article
- Multi-view singular value decomposition for disease subtyping and genetic associations.BMC genetics · 2014Article
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3 authors.
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Abstract
Genetic association analysis of complex diseases has been limited by heterogeneity in their clinical manifestations and genetic etiology. Research has made it possible to differentiate homogeneous subtypes of the disease phenotype. Currently, the most sophisticated subtyping methods perform unsupervised cluster analysis using only clinical features of a disorder, resulting in subtypes for which genetic association may be limited. In this study, we seek to derive a novel multiview data analytic method that integrates two views of the data: the clinical features and the genetic markers of the same set of patients. Our method is based on multiobjective programming that is capable of clinically categorizing a disease phenotype so as to discover genetically different subtypes.We optimize two objectives jointly: 1) in cluster analysis, the derived clusters should differ significantly in clinical features; 2) these clusters can be well separated using genetic markers by constructed classifiers. Extensive computational experiments with two substance-use disorders using two populations show that the proposed algorithm is superior to existing subtyping methods.
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