Division of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
Department of Mathematics & Statistics, Boston University, Boston, MA, USA.
Genome Biol. 2020 Mar 5;21(1):57. doi: 10.1186/s13059-020-1950-6.
Droplet-based microfluidic devices have become widely used to perform single-cell RNA sequencing (scRNA-seq). However, ambient RNA present in the cell suspension can be aberrantly counted along with a cell's native mRNA and result in cross-contamination of transcripts between different cell populations. DecontX is a novel Bayesian method to estimate and remove contamination in individual cells. DecontX accurately predicts contamination levels in a mouse-human mixture dataset and removes aberrant expression of marker genes in PBMC datasets. We also compare the contamination levels between four different scRNA-seq protocols. Overall, DecontX can be incorporated into scRNA-seq workflows to improve downstream analyses.
基于液滴的微流控设备已广泛用于进行单细胞 RNA 测序（scRNA-seq）。然而，细胞悬浮液中存在的环境 RNA 可能会与细胞内源性 mRNA 一起异常计数，并导致不同细胞群体之间的转录本交叉污染。DecontX 是一种估计和去除单个细胞污染的新型贝叶斯方法。DecontX 可准确预测小鼠-人类混合数据集的污染水平，并去除 PBMC 数据集中小鼠标记基因的异常表达。我们还比较了四种不同 scRNA-seq 方案之间的污染水平。总体而言，DecontX 可以整合到 scRNA-seq 工作流程中，以改善下游分析。
