Decoding Heterogenous Single-cell Perturbation Responses.

Area of Science:

• Single-cell biology
• Systems biology
• Genomics

Background:

• Understanding cellular heterogeneity in response to perturbations is crucial for biology and medicine.
• Existing methods lack precision in quantifying perturbation strength and deriving insights from response variations.
• Single-cell transcriptomics generates complex datasets requiring advanced analytical tools.

Approach:

• Introduced the perturbation-response score (PS), a novel method based on constrained quadratic optimization.
• Applied PS to large-scale genetic perturbation datasets (e.g., Perturb-seq) for single-cell analysis.
• Developed PS to quantify perturbation responses, enabling dosage analysis and identification of response determinants.

Key Points:

• PS accurately quantifies partial gene perturbation responses, outperforming current methods in single-cell transcriptomic data.
• PS facilitates large-scale, single-cell dosage analysis of perturbations without requiring titration.
• PS identifies intrinsic and extrinsic factors influencing cellular responses and uncovers novel biological roles, such as CCDC6 in lineage decisions.

Conclusions:

• The perturbation-response score (PS) offers an innovative approach for dose-to-function analysis in single-cell perturbation studies.
• PS enables new biological discoveries by analyzing heterogeneity and dose-response patterns in cellular systems.
• This method advances the understanding of gene function and cellular differentiation processes.