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...

Full description

Saved in:
Bibliographic Details
Published in:Computational and structural biotechnology journal Vol. 19; pp. 3796 - 3798
Main Authors: Andreatta, Massimo, Carmona, Santiago J.
Format: Journal Article
Language:English
Published: Elsevier B.V 01.01.2021
Research Network of Computational and Structural Biotechnology
Elsevier
Subjects:
biotechnology
Cell type
data collection
Gene set enrichment
Gene signature
genes
memory
Module scoring
Single-cell
Gene signature
Gene set enrichment
Module scoring
Cell type
Single-cell
ISSN:2001-0370, 2001-0370
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2001-0370
2001-0370
DOI:10.1016/j.csbj.2021.06.043