生物导体
计算机科学
软件
仿形(计算机编程)
数据科学
计算生物学
可视化
数据挖掘
软件工程
生物
操作系统
生物化学
基因
作者
Robert A. Amezquita,Aaron T. L. Lun,Étienne Becht,Vince Carey,Lindsay N. Carpp,Ludwig Geistlinger,Fédérico Marini,Kévin Rue-Albrecht,Davide Risso,Charlotte Soneson,Levi Waldron,Hervé Pagès,Mike L. Smith,Wolfgang Huber,Martin Morgan,Raphaël Gottardo,Stephanie C. Hicks
出处
期刊:Nature Methods
[Springer Nature]
日期:2019-12-02
卷期号:17 (2): 137-145
被引量:634
标识
DOI:10.1038/s41592-019-0654-x
摘要
Recent technological advancements have enabled the profiling of a large number of genome-wide features in individual cells. However, single-cell data present unique challenges that require the development of specialized methods and software infrastructure to successfully derive biological insights. The Bioconductor project has rapidly grown to meet these demands, hosting community-developed open-source software distributed as R packages. Featuring state-of-the-art computational methods, standardized data infrastructure and interactive data visualization tools, we present an overview and online book ( https://osca.bioconductor.org ) of single-cell methods for prospective users. This Perspective highlights open-source software for single-cell analysis released as part of the Bioconductor project, providing an overview for users and developers.
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