DMLS Lab of Statistical Bioinformatics, University of Zürich, Zürich, 805, Switzerland.
D-HEST Institute for Neuroscience, ETH Zürich, Zürich, Switzerland.
F1000Res. 2021 Sep 28;10:979. doi: 10.12688/f1000research.73600.2. eCollection 2021.
Doublets are prevalent in single-cell sequencing data and can lead to artifactual findings. A number of strategies have therefore been proposed to detect them. Building on the strengths of existing approaches, we developed , a fast, flexible and accurate Bioconductor-based doublet detection method. Here we present the method, justify its design choices, demonstrate its performance on both single-cell RNA and accessibility (ATAC) sequencing data, and provide some observations on doublet formation, detection, and enrichment analysis. Even in complex datasets, can accurately identify most heterotypic doublets, and was already found by an independent benchmark to outcompete alternatives.
二聚体在单细胞测序数据中很常见，可能导致虚假发现。因此，已经提出了许多策略来检测它们。我们在现有方法的优势基础上，开发了一种快速、灵活、准确的基于 Bioconductor 的二聚体检测方法。在这里，我们介绍了该方法，说明了其设计选择的合理性，展示了其在单细胞 RNA 和可及性（ATAC）测序数据上的性能，并对二聚体的形成、检测和富集分析进行了一些观察。即使在复杂的数据集，也可以准确识别大多数异质二聚体，并且已经通过独立的基准测试发现它优于其他方法。
