Scrublet: Computational Identification of Cell Doublets in Single-Cell Transcriptomic Data.

ABSTRACT: Single-cell RNA-sequencing has become a widely used, powerful approach for studying cell populations. However, these methods often generate multiplet artifacts, where two or more cells receive the same barcode, resulting in a hybrid transcriptome. In most experiments, multiplets account for several percent of transcriptomes and can confound downstream data analysis. Here, we present Single-Cell Remover of Doublets (Scrublet), a framework for predicting the impact of multiplets in a given analysis and identifying problematic multiplets. Scrublet avoids the need for expert knowledge or cell clustering by simulating multiplets from the data and building a nearest neighbor classifier. To demonstrate the utility of this approach, we test Scrublet on several datasets that include independent kno

SUBMITTER: Wolock SL 

PROVIDER: S-EPMC6625319 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature