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Orchestrating single-cell analysis with Bioconductor.
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.
Afiliação
  • Amezquita RA; Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Lun ATL; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
  • Becht E; Bioinformatics and Computational Biology, Genentech Inc., San Francisco, CA, USA.
  • Carey VJ; Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Carpp LN; Channing Division of Network Medicine, Brigham And Women's Hospital, Boston, MA, USA.
  • Geistlinger L; Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Marini F; Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA.
  • Rue-Albrecht K; Institute for Implementation Science in Population Health, City University of New York, New York, NY, USA.
  • Risso D; Center for Thrombosis and Hemostasis, Mainz, Germany.
  • Soneson C; Institute of Medical Biostatistics, Epidemiology and Informatics, Mainz, Germany.
  • Waldron L; Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK.
  • Pagès H; Department of Statistical Sciences, University of Padua, Padua, Italy.
  • Smith ML; Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, NY, USA.
  • Huber W; Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
  • Morgan M; SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
  • Gottardo R; Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA.
  • Hicks SC; Institute for Implementation Science in Population Health, City University of New York, New York, NY, USA.
Nat Methods ; 17(2): 137-145, 2020 02.
Article em En | MEDLINE | ID: mdl-31792435
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise de Célula Única Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise de Célula Única Idioma: En Ano de publicação: 2020 Tipo de documento: Article