Orchestrating single-cell analysis with Bioconductor

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....

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Veröffentlicht in:Nature methods 2020-02, Vol.17 (2), p.137-145
Hauptverfasser: Amezquita, Robert A., Lun, Aaron T. L., Becht, Etienne, Carey, Vince J., Carpp, Lindsay N., Geistlinger, Ludwig, Marini, Federico, Rue-Albrecht, Kevin, Risso, Davide, Soneson, Charlotte, Waldron, Levi, Pagès, Hervé, Smith, Mike L., Huber, Wolfgang, Morgan, Martin, Gottardo, Raphael, Hicks, Stephanie C.
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Sprache:eng
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Zusammenfassung: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.
ISSN:1548-7091
1548-7105
DOI:10.1038/s41592-019-0654-x