sSNAPPY

sSNAPPY propagates changes in gene expression down gene-set topologies to compute single-sample directional pathway perturbation scores for RNA-seq data.

Key Features:

• Single-sample directional pathway perturbation scoring: Computes perturbation scores that reflect the potential direction of change for individual samples.
• Gene-set topology propagation: Propagates expression changes through pathway structures rather than treating gene sets as simple collections.
• Multi-level significance testing: Perturbation scores enable testing of pathway perturbation significance at both individual-sample and treatment levels.

Scientific Applications:

• RNA-seq pathway analysis: Identifies directionally perturbed pathways from single-sample gene expression data.
• Individual sample characterization: Enables detection of pathway-level changes in specific samples rather than requiring group averages.
• Treatment effect evaluation: Supports aggregation of single-sample scores to assess pathway perturbation at the treatment or condition level.

Methodology:

The method propagates changes in gene expression down gene-set topologies to compute directional perturbation scores.