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UCell: Robust and scalable single-cell gene signature scoring
- 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
- Subjects :
- Gene set enrichment
Computer science
Biophysics
computer.software_genre
Biochemistry
Data matrix (multivariate statistics)
03 medical and health sciences
0302 clinical medicine
Documentation
Structural Biology
Module scoring
Genetics
Gene signature
030304 developmental biology
0303 health sciences
Single-cell
Signature (logic)
Computer Science Applications
R package
Cell type
030220 oncology & carcinogenesis
Scalability
Data mining
computer
TP248.13-248.65
Research Article
Biotechnology
Subjects
Details
- Language :
- English
- ISSN :
- 20010370
- Volume :
- 19
- Database :
- OpenAIRE
- Journal :
- Computational and Structural Biotechnology Journal
- Accession number :
- edsair.doi.dedup.....baf834e96574c43ffcf60bfa46d0d5d7