Abstract
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 scDblFinder, 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, scDblFinder can accurately identify most heterotypic doublets, and was already found by an independent benchmark to outcompete alternatives.
Funder
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Subject
General Pharmacology, Toxicology and Pharmaceutics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine
Cited by
177 articles.
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