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

机译:Soupx从液滴的单细胞RNA测序数据中除去环境RNA污染

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Abstract 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.
机译:摘要基于背景液滴的单细胞RNA序列分析假设所有获得的RNA都对细胞内源性。然而,这些测定也捕获了输入溶液内包含的任何细胞的RNA。这种无细胞RNA的测序构成了背景污染,使单细胞转发组数据的生物学解释困扰。结果我们表明,无细胞RNA的这种“汤”的污染是普遍存在的,具有实验特异性的组成和幅度的变化。我们介绍了一种方法,汤,用于量化污染的程度和估计“背景校正”的细胞表达配置文件,可以与现有的下游分析工具无缝集成。使用多个液滴排序技术将此方法应用于多个数据集,我们证明其应用程序改善了其他误导性数据的生物解释,以及改善质量控制度量。结论我们呈现SoupX,一种用于从基于液滴的单细胞RNA测序实验中去除环境RNA污染的工具。该工具具有广泛的适用性,其应用可以改善现有和未来数据集的生物效用。

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