  The existence of doublets is a key confounder in single-cell RNA sequencing
(scRNA-seq) data analysis. The scRNA-seq community has developed many
computational methods to detect doublets from scRNA-seq data. Previously, we
conducted a benchmark study to evaluate nine state-of-the-art computational
doublet-detection methods. Here, we summarize our benchmarking procedures into
a protocol for researchers to systematically benchmark doublet-detection
methods in terms of detection accuracy, impacts on downstream analyses, and
computational efficiency. This protocol can accommodate new doublet-detection
methods in the fast-growing scRNA-seq field. Here we include scDblFinder, a new
method that was not in our previous benchmark study.
