Beyondcell

Beyondcell analyzes single-cell RNA sequencing (scRNA-seq) data to identify tumor cell subpopulations with distinct drug-response signatures and to prioritize candidate therapeutics.

Key Features:

• Enrichment Score Calculation: Computes an enrichment score across a collection of drug signatures to delineate therapeutic clusters (TCs) within cellular populations.
• Therapeutic Cluster Identification: Identifies TCs that represent groups of cells with similar drug-response profiles.
• Differential Sensitivity Analysis: Assesses therapeutic differences among cell populations to reveal heterogeneity in drug sensitivity.
• Drug Ranking and Selection: Ranks and prioritizes drugs based on differential sensitivity between chosen conditions to guide selection of candidate therapeutics.

Scientific Applications:

• Oncology research: Aids development of personalized cancer treatments by identifying tumor subpopulations likely to respond to specific drugs.
• Validation and models: Applied to four single-cell datasets and demonstrated utility in both in vitro (cancer cell lines) and in vivo (tumor patients) contexts.

Methodology:

Integrates drug signature data with scRNA-seq datasets and calculates enrichment scores that reflect how well a drug signature matches the gene expression profile of each cellular cluster to identify patterns and correlations indicative of differential drug responses among tumor cell subpopulations.