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miRSCAPE - inferring miRNA expression from scRNA-seq data.
Olgun, Gulden; Gopalan, Vishaka; Hannenhalli, Sridhar.
Afiliação
  • Olgun G; Cancer Data Science Lab, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
  • Gopalan V; Cancer Data Science Lab, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
  • Hannenhalli S; Cancer Data Science Lab, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
iScience ; 25(9): 104962, 2022 Sep 16.
Article em En | MEDLINE | ID: mdl-36060076
Our understanding of miRNA activity at cellular resolution is thwarted by the inability of standard scRNA-seq protocols to capture miRNAs. We introduce a novel tool, miRSCAPE, to infer miRNA expression in a sample from its RNA-seq profile. We establish miRSCAPE's accuracy in 10 tumor and normal cohorts demonstrating its superiority over alternatives. miRSCAPE accurately infers cell type-specific miRNA activities (predicted versus observed fold-difference correlation ∼0.81) in two independent scRNA-seq datasets. We apply miRSCAPE to infer miRNA activities in scRNA clusters in pancreatic and lung adenocarcinomas, as well as in 56 cell types in the human cell landscape (HCL). In pancreatic and breast cancer scRNA-seq data, miRSCAPE recapitulates miRNAs associated with stemness and epithelial-mesenchymal transition (EMT) cell states, respectively. Overall, miRSCAPE recapitulates and refines miRNA biology at cellular resolution. miRSCAPE is freely available and is easily applicable to scRNA-seq data to infer miRNA activities at cellular resolution.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article