Vaeda computationally annotates doublets in single-cell RNA sequencing data.

ABSTRACT:

Motivation

Single-cell RNA sequencing (scRNA-seq) continues to expand our knowledge by facilitating the study of transcriptional heterogeneity at the level of single cells. Despite this technology's utility and success in biomedical research, technical artifacts are present in scRNA-seq data. Doublets/multiplets are a type of artifact that occurs when two or more cells are tagged by the same barcode, and therefore they appear as a single cell. Because this introduces non-existent transcriptional profiles, doublets can bias and mislead downstream analysis. To address this limitation, computational methods to annotate and remove doublets form scRNA-seq datasets are needed.

Results

We introduce vaeda (Variational Auto-Encoder for Doublet Annotation), a new approach for computat

SUBMITTER: Schriever H 

PROVIDER: S-EPMC9805559 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature