EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays

EmptyDropsMultiome可在单细胞多组学分析中区分真实细胞和背景细胞。

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Abstract

Multiomic droplet-based technologies allow different molecular modalities, such as chromatin accessibility and gene expression (scATAC-seq and scRNA-seq), to be probed in the same nucleus. We develop EmptyDropsMultiome, an approach that distinguishes true nuclei-containing droplets from background. Using simulations, we show that EmptyDropsMultiome has higher statistical power and accuracy than existing approaches, including CellRanger-arc and EmptyDrops. On real datasets, we observe that CellRanger-arc misses more than half of the nuclei identified by EmptyDropsMultiome and, moreover, is biased against certain cell types, some of which have a retrieval rate lower than 20%.

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