EnClaSC: a novel ensemble approach for accurate and robust cell-type classification of single-cell transcriptomes.

Chen, Xiaoyang; Chen, Shengquan; Jiang, Rui

Chen, Xiaoyang; Chen, Shengquan; Jiang, Rui.

Afiliação

Chen X; MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University, Beijing, 100084, China.
Chen S; MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University, Beijing, 100084, China.
Jiang R; MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University, Beijing, 100084, China. ruijiang@tsinghua.edu.cn.

BMC Bioinformatics ; 21(Suppl 13): 392, 2020 Sep 17.

Article em En | MEDLINE | ID: mdl-32938367

Assuntos

Análise de Célula Única/métodos; Transcriptoma/genética; Humanos; Projetos de Pesquisa

Palavras-chave

Cell types; Classification; Feature selection; Few-sample classes; Neural networks; Single-cell; scRNA-seq

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise de Célula Única / Transcriptoma Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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