title: Metrical Consistency NMF for Predicting Gene-Phenotype Associations.
abstract: Discovering gene-phenotype associations is significant to understand the disease mechanisms. Nonnegative matrix factorization (NMF) has been widely used in computational biology for its good performance and interpretability. In this paper, we proposed a novel metrical consistency NMF (MCNMF) method for candidate gene prioritization. The MCNMF method assume that phenotype similarities, calculated from various independent ways, should be consistent in case that the associations between genes and phenotypes are completely known. Experiment results show that our method can recover the gene-phenotype associations effectively and outperform the comparative methods.
authors.affiliation: College of Software, Nankai University, Tianjin, 300350, China.
authors.forename: Shuai
authors.initials: S
authors.lastname: Han
authors.affiliation: College of Software, Nankai University, Tianjin, 300350, China.
authors.forename: Hong
authors.initials: H
authors.lastname: Cai
authors.affiliation: College of Software, Nankai University, Tianjin, 300350, China.
authors.forename: Dan
authors.initials: D
authors.lastname: Che
authors.affiliation: College of Software, Nankai University, Tianjin, 300350, China.
authors.forename: Yaogong
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: College of Software, Nankai University, Tianjin, 300350, China.
authors.forename: Yalou
authors.initials: Y
authors.lastname: Huang
authors.affiliation: College of Software, Nankai University, Tianjin, 300350, China. xiemq@nankai.edu.cn.
authors.forename: Maoqiang
authors.identifier: http://orcid.org/0000-0002-6335-5744
authors.initials: M
authors.lastname: Xie
mesh_terms: D000465:Algorithms; D056726:Genetic Association Studies; D006801:Humans; D010641:Phenotype; D025941:Protein Interaction Mapping
keywords: Gene–phenotype associations; Metrical consistency; NMF; Phenotype similarity