SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data.


Journal

GigaScience
ISSN: 2047-217X
Titre abrégé: Gigascience
Pays: United States
ID NLM: 101596872

Informations de publication

Date de publication:
26 12 2020
Historique:
received: 03 02 2020
revised: 13 10 2020
accepted: 27 11 2020
entrez: 28 12 2020
pubmed: 29 12 2020
medline: 26 10 2021
Statut: ppublish

Résumé

Droplet-based single-cell RNA sequence analyses assume that all acquired RNAs are endogenous to cells. However, any cell-free RNAs contained within the input solution are also captured by these assays. This sequencing of cell-free RNA constitutes a background contamination that confounds the biological interpretation of single-cell transcriptomic data. We demonstrate that contamination from this "soup" of cell-free RNAs is ubiquitous, with experiment-specific variations in composition and magnitude. We present a method, SoupX, for quantifying the extent of the contamination and estimating "background-corrected" cell expression profiles that seamlessly integrate with existing downstream analysis tools. Applying this method to several datasets using multiple droplet sequencing technologies, we demonstrate that its application improves biological interpretation of otherwise misleading data, as well as improving quality control metrics. We present SoupX, a tool for removing ambient RNA contamination from droplet-based single-cell RNA sequencing experiments. This tool has broad applicability, and its application can improve the biological utility of existing and future datasets.

Sections du résumé

BACKGROUND
Droplet-based single-cell RNA sequence analyses assume that all acquired RNAs are endogenous to cells. However, any cell-free RNAs contained within the input solution are also captured by these assays. This sequencing of cell-free RNA constitutes a background contamination that confounds the biological interpretation of single-cell transcriptomic data.
RESULTS
We demonstrate that contamination from this "soup" of cell-free RNAs is ubiquitous, with experiment-specific variations in composition and magnitude. We present a method, SoupX, for quantifying the extent of the contamination and estimating "background-corrected" cell expression profiles that seamlessly integrate with existing downstream analysis tools. Applying this method to several datasets using multiple droplet sequencing technologies, we demonstrate that its application improves biological interpretation of otherwise misleading data, as well as improving quality control metrics.
CONCLUSIONS
We present SoupX, a tool for removing ambient RNA contamination from droplet-based single-cell RNA sequencing experiments. This tool has broad applicability, and its application can improve the biological utility of existing and future datasets.

Identifiants

pubmed: 33367645
pii: 6049831
doi: 10.1093/gigascience/giaa151
pmc: PMC7763177
pii:
doi:

Substances chimiques

RNA 63231-63-0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press GigaScience.

Références

Nature. 2019 Oct;574(7778):365-371
pubmed: 31597962
Cell. 2015 May 21;161(5):1202-1214
pubmed: 26000488
Nat Commun. 2017 Dec 11;8(1):2128
pubmed: 29225342
Sci Rep. 2017 Oct 27;7(1):14225
pubmed: 29079795
Sci Rep. 2017 Mar 31;7:45656
pubmed: 28361918
Nat Protoc. 2017 Jan;12(1):44-73
pubmed: 27929523
Genome Biol. 2016 Feb 17;17:29
pubmed: 26887813
Nat Methods. 2020 Jun;17(6):615-620
pubmed: 32366989
EMBO J. 2017 Dec 15;36(24):3619-3633
pubmed: 29030486
Nat Commun. 2017 Jan 16;8:14049
pubmed: 28091601
Nat Biotechnol. 2015 May;33(5):495-502
pubmed: 25867923
Nat Biotechnol. 2018 Jun;36(5):411-420
pubmed: 29608179
Sci Data. 2018 Feb 13;5:180013
pubmed: 29437159
Nat Biotechnol. 2018 Jun;36(5):421-427
pubmed: 29608177
Cell Syst. 2019 Apr 24;8(4):281-291.e9
pubmed: 30954476
Nat Methods. 2017 Apr;14(4):381-387
pubmed: 28263961
Genome Biol. 2020 Mar 5;21(1):57
pubmed: 32138770
Nat Commun. 2018 Feb 23;9(1):791
pubmed: 29476078
Nature. 2017 Oct 18;550(7677):451-453
pubmed: 29072289
Science. 2018 Aug 10;361(6402):594-599
pubmed: 30093597

Auteurs

Matthew D Young (MD)

Wellcome Trust Sanger Institute, Cellular Genetics, Wellcome Genome Campus, Hinxton, CB10 1SA, UK.

Sam Behjati (S)

Wellcome Trust Sanger Institute, Cellular Genetics, Wellcome Genome Campus, Hinxton, CB10 1SA, UK.
Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge, CB2 0QQ, UK.
University of Cambridge, Department of Paediatrics, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.

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Classifications MeSH