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SANTA: quantifying the functional content of molecular networks.

Published version
Peer-reviewed

Repository DOI


Type

Article

Change log

Authors

Cornish, Alex J 

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 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.

Description

Keywords

Cell Line, Tumor, Gene Regulatory Networks, Humans, Models, Biological, Models, Molecular, RNA Interference, Saccharomyces cerevisiae, Signal Transduction, Systems Biology

Journal Title

PLoS Comput Biol

Conference Name

Journal ISSN

1553-734X
1553-7358

Volume Title

10

Publisher

Public Library of Science (PLoS)
Sponsorship
Cancer Research UK (C14303/A17197)
Cancer Research UK (CB4320)
We acknowledge support by the University of Cambridge, Cancer Research UK, and Hutchison Whampoa Limited.