Improving doublet cell removal efficiency through multiple algorithm runs.

ABSTRACT: Doublets are a key confounding factor in the analysis of scRNA-seq data, as they can interfere with differential expression analysis and disrupt developmental trajectories. However, due to the randomness of the algorithms, most doublet removal methods still leave a certain proportion of doublets after application. In this study, we proposed a multi-round doublet removal (MRDR) strategy, that ran the algorithm in cycles multiple times to effectively reduce randomness while enhancing the effectiveness of doublet removal. We evaluated the MRDR strategy in 14 real-world datasets, 29 barcoded scRNA-seq datasets, and 106 synthetic datasets with four popular doublet detection tools, including DoubletFinder, cxds, bcds, and hybrid. We found that in real-world datasets, the DoubletFinder had a bett

SUBMITTER: She Y 

PROVIDER: S-EPMC11794957 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature