SANTA: quantifying the functional content of molecular networks

TL;DR

SANTA is a statistical method that quantifies the association between molecular networks and cellular functions, enabling functional annotation and gene prioritization in systems biology.

Contribution

It adapts spatial statistics concepts to assess network-function associations, providing a new tool for network annotation and gene analysis.

Findings

Successfully annotated yeast genetic networks and cancer cell line screens.

Demonstrated the method's ability to prioritize genes for follow-up studies.

Validated SANTA's statistical robustness through simulations and case studies.

Abstract

Linking networks of molecular interactions to cellular functions and phenotypes is a key goal in systems biology. Here, we adapt concepts of spatial statistics to assess the functional content of molecular networks. Based on the guilt-by-association principle, our approach (called SANTA) quantifies the strength of association between a gene set and a network, and functionally annotates molecular networks like other enrichment methods annotate lists of genes. As a general association measure, SANTA can (i) functionally annotate experimentally derived networks using a collection of curated gene sets, and (ii) annotate experimentally derived gene sets using a collection of curated networks, as well as (iii) prioritize genes for follow-up analyses. We exemplify the efficacy of SANTA in several case studies using the \emph{S. cerevisiae} genetic interaction network and genome-wide RNAi screens in cancer cell lines. Our theory, simulations and applications show that SANTA provides a principled statistical way to quantify the association between molecular networks and cellular functions and phenotypes. SANTA is available from http://bioconductor.org/packages/release/bioc/html/SANTA.html.