UCell: Robust and scalable single-cell gene signature scoring

Massimo Andreatta; Santiago J Carmona

doi:10.1016/j.csbj.2021.06.043

UCell: Robust and scalable single-cell gene signature scoring

Comput Struct Biotechnol J. 2021 Jun 30:19:3796-3798. doi: 10.1016/j.csbj.2021.06.043. eCollection 2021.

Authors

Massimo Andreatta^{1

2}, Santiago J Carmona^{1

2}

Affiliations

¹ Ludwig Institute for Cancer Research, Lausanne Branch, and Department of Oncology, CHUV and University of Lausanne, Epalinges 1066, Switzerland.
² Swiss Institute of Bioinformatics, Lausanne, Switzerland.

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.