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

核糖核酸 污染 转录组 计算生物学 细胞 信使核糖核酸 RNA提取 生物 计算机科学 基因表达 基因 遗传学 生态学
作者
Matthew D. Young,Sam Behjati
标识
DOI:10.1101/303727
摘要

Abstract Background 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 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 data sets. Key Points The signal from droplet based single cell RNA sequencing is ubiquitously contaminated by capture of ambient mRNA. SoupX is a method to quantify the abundance of these ambient mRNAs and remove them. Correcting for ambient mRNA contamination improves biological interpretation.

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