ScAnnotatR: framework to accurately classify cell types in single-cell RNA-sequencing data.

ABSTRACT:

Background

Automatic cell type identification is essential to alleviate a key bottleneck in scRNA-seq data analysis. While most existing classification tools show good sensitivity and specificity, they often fail to adequately not-classify cells that are missing in the used reference. Additionally, many tools do not scale to the continuously increasing size of current scRNA-seq datasets. Therefore, additional tools are needed to solve these challenges.

Results

scAnnotatR is a novel R package that provides a complete framework to classify cells in scRNA-seq datasets using pre-trained classifiers. It supports both Seurat and Bioconductor's SingleCellExperiment and is thereby compatible with the vast majority of R-based analysis workflows. scAnnotatR uses hierarchically organis

SUBMITTER: Nguyen V 

PROVIDER: S-EPMC8762856 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature