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SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data
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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763177/ https://www.ncbi.nlm.nih.gov/pubmed/33367645 http://dx.doi.org/10.1093/gigascience/giaa151 |
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author | Young, Matthew D Behjati, Sam |
author_facet | Young, Matthew D Behjati, Sam |
author_sort | Young, Matthew D |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7763177 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77631772020-12-31 SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data Young, Matthew D Behjati, Sam Gigascience Technical Note 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. Oxford University Press 2020-12-26 /pmc/articles/PMC7763177/ /pubmed/33367645 http://dx.doi.org/10.1093/gigascience/giaa151 Text en © The Author(s) 2020. Published by Oxford University Press GigaScience. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technical Note Young, Matthew D Behjati, Sam SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data |
title | SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data |
title_full | SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data |
title_fullStr | SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data |
title_full_unstemmed | SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data |
title_short | SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data |
title_sort | soupx removes ambient rna contamination from droplet-based single-cell rna sequencing data |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763177/ https://www.ncbi.nlm.nih.gov/pubmed/33367645 http://dx.doi.org/10.1093/gigascience/giaa151 |
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