TWO-SIGMA: A novel two-component single cell model-based association method for single-cell RNA-seq data.

Van Buren, Eric; Hu, Ming; Weng, Chen; Jin, Fulai; Li, Yan; Wu, Di; Li, Yun

Van Buren, Eric; Hu, Ming; Weng, Chen; Jin, Fulai; Li, Yan; Wu, Di; Li, Yun.

Afiliação

Van Buren E; Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Hu M; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Weng C; Department of Genetics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.
Jin F; Department of Genetics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.
Li Y; Department of Genetics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.
Wu D; Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Li Y; Division of Oral and Craniofacial Health Sciences, Adams School of Dentistry, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Genet Epidemiol ; 45(2): 142-153, 2021 03.

Article em En | MEDLINE | ID: mdl-32989764

Assuntos

Perfilação da Expressão Gênica; Análise de Célula Única; Humanos; Modelos Genéticos; RNA-Seq; Análise de Sequência de RNA; Software

Palavras-chave

differential expression; random effects model; single-cell RNA sequencing; zero-inflated model

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Perfilação da Expressão Gênica / Análise de Célula Única Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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