Doublet identification in single-cell sequencing data using scDblFinder

Abstract

<ns5:p> 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 <ns5:italic>scDblFinder</ns5:italic> , 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 sequencing data, and provide some observations on doublet formation, detection, and enrichment analysis. Even in complex datasets, <ns5:italic>scDblFinder</ns5:italic> can accurately identify most heterotypic doublets, and was already found by an independent benchmark to outcompete alternatives. </ns5:p>