Enabling Single-Cell Drug Response Annotations from Bulk RNA-Seq Using SCAD.

ABSTRACT: The single-cell RNA sequencing (scRNA-seq) quantifies the gene expression of individual cells, while the bulk RNA sequencing (bulk RNA-seq) characterizes the mixed transcriptome of cells. The inference of drug sensitivities for individual cells can provide new insights to understand the mechanism of anti-cancer response heterogeneity and drug resistance at the cellular resolution. However, pharmacogenomic information related to their corresponding scRNA-Seq is often limited. Therefore, a transfer learning model is proposed to infer the drug sensitivities at single-cell level. This framework learns bulk transcriptome profiles and pharmacogenomics information from population cell lines in a large public dataset and transfers the knowledge to infer drug efficacy of individual cells. The resul

SUBMITTER: Zheng Z 

PROVIDER: S-EPMC10104628 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature