Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single cell RNA-sequencing datasets.

Maden, Sean K; Kwon, Sang Ho; Huuki-Myers, Louise A; Collado-Torres, Leonardo; Hicks, Stephanie C; Maynard, Kristen R

Maden, Sean K; Kwon, Sang Ho; Huuki-Myers, Louise A; Collado-Torres, Leonardo; Hicks, Stephanie C; Maynard, Kristen R.

Afiliação

Maden SK; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Kwon SH; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
Huuki-Myers LA; The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Collado-Torres L; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
Hicks SC; Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
Maynard KR; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

ArXiv ; 2023 May 10.

Article em En | MEDLINE | ID: mdl-37214135

Palavras-chave

Deconvolution; cell sizes; single cell RNA-sequencing; single nucleus RNA-sequencing

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ArXiv Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

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