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

Matthew D. Young, Sam Behjati
doi: https://doi.org/10.1101/303727
Matthew D. Young
1Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
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Sam Behjati
1Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
2Cambridge University Hospitals NHS Foundation Trust, Cambridge, CB2 0QQ, UK
3Department of Paediatrics, University of Cambridge, Cambridge, CB2 0QQ, UK
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Abstract

Droplet based single cell RNA sequence analyses assume 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 has the potential to confound the correct biological interpretation of single cell transcriptomic data. Here, we demonstrate that contamination from this “soup” of cell free RNAs is ubiquitous, experiment specific in its composition and magnitude, and can lead to erroneous biological conclusions. We present a method, SoupX, for quantifying the extent of the contamination and estimating “background corrected”, cell expression profiles that can be integrated with existing downstream analysis tools. We apply this method to two data-sets and show that the application of this method reduces batch effects, strengthens cell-specific quality control and improves biological interpretation

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 20, 2018.
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SoupX removes ambient RNA contamination from droplet based single cell RNA sequencing data
Matthew D. Young, Sam Behjati
bioRxiv 303727; doi: https://doi.org/10.1101/303727
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SoupX removes ambient RNA contamination from droplet based single cell RNA sequencing data
Matthew D. Young, Sam Behjati
bioRxiv 303727; doi: https://doi.org/10.1101/303727

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