Open AccessOrchestrating single-cell analysis with Bioconductor
Author(s) -
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 Hicks
Publication year - 2019
Publication title -
nature methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 19.469
H-Index - 318
eISSN - 1548-7105
pISSN - 1548-7091
DOI - 10.1038/s41592-019-0654-x
Subject(s) - bioconductor , computer science , software , profiling (computer programming) , visualization , data science , computational biology , data mining , software engineering , biology , operating system , biochemistry , gene
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.