Ploidy inference from single-cell data: application to human and mouse cell atlases.
Genetics
; 227(2)2024 06 05.
Article
em En
| MEDLINE
| ID: mdl-38651869
ABSTRACT
Ploidy is relevant to numerous biological phenomena, including development, metabolism, and tissue regeneration. Single-cell RNA-seq and other omics studies are revolutionizing our understanding of biology, yet they have largely overlooked ploidy. This is likely due to the additional assay step required for ploidy measurement. Here, we developed a statistical method to infer ploidy from single-cell ATAC-seq data, addressing this gap. When applied to data from human and mouse cell atlases, our method enabled systematic detection of polyploidy across diverse cell types. This method allows for the integration of ploidy analysis into single-cell studies. Additionally, this method can be adapted to detect the proliferating stage in the cell cycle and copy number variations in cancer cells. The software is implemented as the scPloidy package of the R software and is freely available from CRAN.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Ploidias
/
Software
/
Análise de Célula Única
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Genetics
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Austrália
País de publicação:
Estados Unidos