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UCell: Robust and scalable single-cell gene signature scoring

Authors :
Massimo Andreatta
Santiago J. Carmona
Source :
Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 3796-3798 (2021), Computational and Structural Biotechnology Journal, Computational and structural biotechnology journal, vol. 19, pp. 3796-3798
Publication Year :
2021
Publisher :
Elsevier, 2021.

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 athttps://github.com/carmonalab/UCell

Details

Language :
English
ISSN :
20010370
Volume :
19
Database :
OpenAIRE
Journal :
Computational and Structural Biotechnology Journal
Accession number :
edsair.doi.dedup.....baf834e96574c43ffcf60bfa46d0d5d7