Benchmarking computational doublet-detection methods for single-cell RNA sequencing data

This repository contains the real and simulation datasets used in the paper "Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data". Please check the full text published on Cell Systems or our preprint.

1. real_datasets.zip: 16 real scRNA-seq datasets with experimentally annotated doublets. The name of each file corresponds to the names in the benchmark paper.

2. simulation_datasets.zip: simulation datasets used in the benchmark, including different experimental conditions, scalability, stability, running time, and the effects of doublet detection on DE gene analysis, highly variable gene identification, cell clustering, and trajectory inference.

3. result.xlsx: a tabular file that saves benchmarking results, including AUPRC, AUROC, precision, recall, TNR, and cell clustering. It is also the data source for drawing figures in the paper "Protocol for Benchmarking Computational Doublet-Detection Methods in Single-Cell RNA Sequencing Data Analysis".