UCell: Robust and scalable single-cell gene signature scoring.

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State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_ADC3FAC598DC
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
UCell: Robust and scalable single-cell gene signature scoring.
Journal
Computational and structural biotechnology journal
Author(s)
Andreatta M., Carmona S.J.
ISSN
2001-0370 (Print)
ISSN-L
2001-0370
Publication state
Published
Issued date
2021
Peer-reviewed
Oui
Volume
19
Pages
3796-3798
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
UCell is an R package for evaluating gene signatures in single-cell datasets. UCell signature scores, based on the Mann-Whitney U statistic, are robust to dataset size and heterogeneity, and their calculation demands less computing time and memory than other available methods, enabling the processing of large datasets in a few minutes even on machines with limited computing power. UCell can be applied to any single-cell data matrix, and includes functions to directly interact with Seurat objects. The UCell package and documentation are available on GitHub at https://github.com/carmonalab/UCell.
Keywords
Cell type, Gene set enrichment, Gene signature, Module scoring, Single-cell
Pubmed
Web of science
Open Access
Yes
Create date
26/07/2021 9:26
Last modification date
12/01/2022 8:12
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