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scRNA-seq for Microcephaly Research [III]: Computational Analysis of scRNA-seq Data.
Babcock, Benjamin; Malawsky, Daniel.
Afiliação
  • Babcock B; Department of Medicine, Division of Immunology, Lowance Center for Human Immunology, Emory University School of Medicine, Atlanta, GA, USA. ben.babcock@emory.edu.
  • Malawsky D; Department of Neurology, University of North Carolina Medical School, Chapel Hill, NC, USA. ben.babcock@emory.edu.
Methods Mol Biol ; 2583: 105-121, 2023.
Article em En | MEDLINE | ID: mdl-36418729
ABSTRACT
Single-cell transcriptomic analysis (scRNA-seq) can enable researchers to explore the gene expression patterns of thousands of individual cells simultaneously. Processing the complex data generated by scRNA-seq requires specialized computational tools. This chapter focuses on the analytical aspect of scRNA-seq workflow, with a focus on resolving biological signals from large-scale scRNA-seq data produced by the Drop-Seq platform.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Microcefalia Limite: Humans Idioma: En Revista: Methods Mol Biol Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Microcefalia Limite: Humans Idioma: En Revista: Methods Mol Biol Ano de publicação: 2023 Tipo de documento: Article