Protocol for executing and benchmarking eight computational doublet-detection methods in single-cell RNA sequencing data analysis

Abstract

Summary: The existence of doublets is a key confounder in single-cell RNA sequencing (scRNA-seq) data analysis. Computational techniques have been developed for detecting doublets from scRNA-seq data. We developed an R package DoubletCollection to integrate the installation and execution of eight doublet detection methods. DoubletCollection provides a unified interface to perform and visualize downstream analysis after doublet detection. Here, we present a protocol of using DoubletCollection to benchmark doublet-detection methods. This protocol can accommodate new doublet-detection methods in the fast-growing scRNA-seq field.For details on the use and execution of this protocol, please refer to Xi and Li (2020).

Keywords

• Bioinformatics
• Sequencing
• RNAseq
• Molecular Biology