SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data
Wellcome Sanger Institute · University of Cambridge · +3 more institutions
Abstract
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.
Citation impact
- FWCI
- 51.35
- Percentile
- 100%
- References
- 24
Authors
2Topics & keywords
- RNA
- Contamination
- Transcriptome
- Computational biology
- Computer science
- Cell
- Biology
- Gene expression
- Life below water