SANTA

SANTA quantifies the strength of association between gene sets and molecular interaction networks using spatial-statistics-derived measures to link networks to cellular functions and phenotypes.

Key Features:

• Functional Annotation: Adapts spatial statistical concepts to functionally annotate molecular networks analogous to gene-set enrichment but applied to network structures.
• Guilt-by-Association Principle: Quantifies clustering of genes or proteins within a network to assess how closely a gene set is associated with specific network regions.
• Dual Annotation Capability: Annotates experimentally derived networks using curated gene sets and conversely annotates experimentally derived gene sets using collections of curated networks.
• Gene Prioritization: Identifies and ranks genes with strong network associations for experimental follow-up.

Scientific Applications:

• Case Studies: Applied to analyses of the Saccharomyces cerevisiae genetic interaction network and genome-wide RNA interference (RNAi) screens in cancer cell lines.
• Systems Biology: Links molecular networks to cellular functions and phenotypes to support systems-level interpretation of biological processes.

Methodology:

SANTA applies spatial-statistics-derived measures to assess clustering and association strengths between gene sets and regions or nodes of molecular networks, providing a principled statistical assessment of functional content.