Comparison of visualization tools for single-cell RNAseq data.
Journal
NAR genomics and bioinformatics
ISSN: 2631-9268
Titre abrégé: NAR Genom Bioinform
Pays: England
ID NLM: 101756213
Informations de publication
Date de publication:
Sep 2020
Sep 2020
Historique:
received:
16
03
2020
revised:
17
06
2020
accepted:
07
07
2020
entrez:
9
8
2020
pubmed:
9
8
2020
medline:
9
8
2020
Statut:
ppublish
Résumé
In the last decade, single cell RNAseq (scRNAseq) datasets have grown in size from a single cell to millions of cells. Due to its high dimensionality, it is not always feasible to visualize scRNAseq data and share it in a scientific report or an article publication format. Recently, many interactive analysis and visualization tools have been developed to address this issue and facilitate knowledge transfer in the scientific community. In this study, we review several of the currently available scRNAseq visualization tools and benchmark the subset that allows to visualize the data on the web and share it with others. We consider the memory and time required to prepare datasets for sharing as the number of cells increases, and additionally review the user experience and features available in the web interface. To address the problem of format compatibility we have also developed a user-friendly R package,
Identifiants
pubmed: 32766548
doi: 10.1093/nargab/lqaa052
pii: lqaa052
pmc: PMC7391988
doi:
Types de publication
Journal Article
Langues
eng
Pagination
lqaa052Subventions
Organisme : Wellcome Trust
Pays : United Kingdom
Informations de copyright
© The Author(s) 2019. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.
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