A comprehensive comparison of supervised and unsupervised methods for cell type identification in single-cell RNA-seq.

Sun, Xiaobo; Lin, Xiaochu; Li, Ziyi; Wu, Hao

Sun, Xiaobo; Lin, Xiaochu; Li, Ziyi; Wu, Hao.

Sun X; Department of Statistics, School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan, Hubei, China.
Lin X; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Li Z; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, U.S.
Wu H; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.

Brief Bioinform ; 23(2)2022 03 10.

Article en En | MEDLINE | ID: mdl-35021202

Asunto(s)

Perfilación de la Expresión Génica; Análisis de la Célula Individual; Algoritmos; Análisis por Conglomerados; Perfilación de la Expresión Génica/métodos; RNA-Seq; Análisis de Secuencia de ARN/métodos; Análisis de la Célula Individual/métodos

Palabras clave

cell type identification; scRNA-seq; supervised learning; unsupervised clustering

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Perfilación de la Expresión Génica / Análisis de la Célula Individual Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article

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