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Decontamination of ambient RNA in single-cell RNA-seq with DecontX

Shiyi Yang, Sean E. Corbett, Yusuke Koga, View ORCID ProfileZhe Wang, W. Evan Johnson, Masanao Yajima, Joshua D. Campbell
doi: https://doi.org/10.1101/704015
Shiyi Yang
1Division of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
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Sean E. Corbett
1Division of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
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Yusuke Koga
1Division of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
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Zhe Wang
1Division of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
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  • ORCID record for Zhe Wang
W. Evan Johnson
1Division of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
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Masanao Yajima
2Department of Mathematics & Statistics, Boston University, Boston, MA, USA
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Joshua D. Campbell
1Division of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
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  • For correspondence: camp@bu.edu
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ABSTRACT

Droplet-based microfluidic devices have become widely used to perform single-cell RNA sequencing (scRNA-seq) and discover novel cellular heterogeneity in complex biological systems. However, ambient RNA present in the cell suspension can be incorporated into these droplets and aberrantly counted along with a cell’s native mRNA. This results in cross-contamination of transcripts between different cell populations and can potentially decrease the precision of downstream analyses. We developed a novel hierarchical Bayesian method called DecontX to estimate and remove contamination in individual cells from scRNA-seq data. DecontX accurately predicted the proportion of contaminated counts in a mixture of mouse and human cells. Decontamination of PBMC datasets removed aberrant expression of cell type specific marker genes from other cell types and improved overall separation of cell clusters. In general, DecontX can be incorporated into scRNA-seq workflows to assess quality of dissociation protocols and improve downstream analyses.

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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 4.0 International license.
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Posted July 16, 2019.
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Decontamination of ambient RNA in single-cell RNA-seq with DecontX
Shiyi Yang, Sean E. Corbett, Yusuke Koga, Zhe Wang, W. Evan Johnson, Masanao Yajima, Joshua D. Campbell
bioRxiv 704015; doi: https://doi.org/10.1101/704015
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Decontamination of ambient RNA in single-cell RNA-seq with DecontX
Shiyi Yang, Sean E. Corbett, Yusuke Koga, Zhe Wang, W. Evan Johnson, Masanao Yajima, Joshua D. Campbell
bioRxiv 704015; doi: https://doi.org/10.1101/704015

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