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UCell: Robust and scalable single-cell gene signature scoring

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 processin...

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Detalles Bibliográficos
Autores principales: Andreatta, Massimo, Carmona, Santiago J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271111/
https://www.ncbi.nlm.nih.gov/pubmed/34285779
http://dx.doi.org/10.1016/j.csbj.2021.06.043
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author Andreatta, Massimo
Carmona, Santiago J.
author_facet Andreatta, Massimo
Carmona, Santiago J.
author_sort Andreatta, Massimo
collection PubMed
description 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.
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spelling pubmed-82711112021-07-19 UCell: Robust and scalable single-cell gene signature scoring Andreatta, Massimo Carmona, Santiago J. Comput Struct Biotechnol J Research Article 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. Research Network of Computational and Structural Biotechnology 2021-06-30 /pmc/articles/PMC8271111/ /pubmed/34285779 http://dx.doi.org/10.1016/j.csbj.2021.06.043 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Andreatta, Massimo
Carmona, Santiago J.
UCell: Robust and scalable single-cell gene signature scoring
title UCell: Robust and scalable single-cell gene signature scoring
title_full UCell: Robust and scalable single-cell gene signature scoring
title_fullStr UCell: Robust and scalable single-cell gene signature scoring
title_full_unstemmed UCell: Robust and scalable single-cell gene signature scoring
title_short UCell: Robust and scalable single-cell gene signature scoring
title_sort ucell: robust and scalable single-cell gene signature scoring
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271111/
https://www.ncbi.nlm.nih.gov/pubmed/34285779
http://dx.doi.org/10.1016/j.csbj.2021.06.043
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