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UCell:强大且可扩展的单细胞基因特征评分

UCell: Robust and scalable single-cell gene signature scoring.

作者信息

Andreatta Massimo, Carmona Santiago J

机构信息

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

Swiss Institute of Bioinformatics, Lausanne, Switzerland.

出版信息

Comput Struct Biotechnol J. 2021 Jun 30;19:3796-3798. doi: 10.1016/j.csbj.2021.06.043. eCollection 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 at https://github.com/carmonalab/UCell.

摘要

UCell是一个用于评估单细胞数据集中基因特征的R软件包。基于曼-惠特尼U统计量的UCell特征分数对数据集大小和异质性具有鲁棒性,并且与其他可用方法相比,其计算所需的时间和内存更少,即使在计算能力有限的机器上也能在几分钟内处理大型数据集。UCell可应用于任何单细胞数据矩阵,并包括与Seurat对象直接交互的函数。UCell软件包和文档可在GitHub上获取,网址为https://github.com/carmonalab/UCell。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/771b/8271111/a8cc59399d18/gr1.jpg

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