Ultra-fast scalable estimation of single-cell differentiation potency from scRNA-Seq data | Zendy

Andrew E. Teschendorff | Zendy; Alok K. Maity | Zendy; Hu Xue | Zendy; Chen Wei-yan | Zendy; Matthias Lechner | Zendy

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Ultra-fast scalable estimation of single-cell differentiation potency from scRNA-Seq data

Author(s) -

Andrew E. Teschendorff,

Alok K. Maity,

Hu Xue,

Chen Wei-yan,

Matthias Lechner

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa987

Subject(s) - potency , scalability , computer science , robustness (evolution) , profiling (computer programming) , computational biology , transcriptome , biology , gene , genetics , database , gene expression , operating system , in vitro

An important task in the analysis of single-cell RNA-Seq data is the estimation of differentiation potency, as this can help identify stem-or-multipotent cells in non-temporal studies or in tissues where differentiation hierarchies are not well established. A key challenge in the estimation of single-cell potency is the need for a fast and accurate algorithm, scalable to large scRNA-Seq studies profiling millions of cells.

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