Besca, a single-cell transcriptomics analysis toolkit to accelerate translational research.

ABSTRACT: Single-cell RNA sequencing (scRNA-seq) revolutionized our understanding of disease biology. The promise it presents to also transform translational research requires highly standardized and robust software workflows. Here, we present the toolkit Besca, which streamlines scRNA-seq analyses and their use to deconvolute bulk RNA-seq data according to current best practices. Beyond a standard workflow covering quality control, filtering, and clustering, two complementary Besca modules, utilizing hierarchical cell signatures and supervised machine learning, automate cell annotation and provide harmonized nomenclatures. Subsequently, the gene expression profiles can be employed to estimate cell type proportions in bulk transcriptomics data. Using multiple, diverse scRNA-seq dataset

SUBMITTER: Madler SC 

PROVIDER: S-EPMC8573822 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature