Orchestrating single-cell analysis with Bioconductor.

Détails

ID Serval
serval:BIB_CC67D1B61149
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Orchestrating single-cell analysis with Bioconductor.
Périodique
Nature methods
Auteur⸱e⸱s
Amezquita R.A., Lun ATL, Becht E., Carey V.J., Carpp L.N., Geistlinger L., Marini F., Rue-Albrecht K., Risso D., Soneson C., Waldron L., Pagès H., Smith M.L., Huber W., Morgan M., Gottardo R., Hicks S.C.
ISSN
1548-7105 (Electronic)
ISSN-L
1548-7091
Statut éditorial
Publié
Date de publication
02/2020
Peer-reviewed
Oui
Volume
17
Numéro
2
Pages
137-145
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
Publication Status: ppublish
Résumé
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.
Mots-clé
Gene Expression Profiling, Genome, High-Throughput Nucleotide Sequencing, Single-Cell Analysis/methods, Software
Pubmed
Web of science
Création de la notice
28/02/2022 11:45
Dernière modification de la notice
23/03/2024 7:24
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