Orchestrating single-cell analysis with Bioconductor.

Details

Serval ID
serval:BIB_CC67D1B61149
Type
Article: article from journal or magazin.
Collection
Publications
Title
Orchestrating single-cell analysis with Bioconductor.
Journal
Nature methods
Author(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
Publication state
Published
Issued date
02/2020
Peer-reviewed
Oui
Volume
17
Number
2
Pages
137-145
Language
english
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
Publication Status: ppublish
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.
Keywords
Gene Expression Profiling, Genome, High-Throughput Nucleotide Sequencing, Single-Cell Analysis/methods, Software
Pubmed
Web of science
Create date
28/02/2022 11:45
Last modification date
23/03/2024 7:24
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