PT  - JOURNAL ARTICLE
AU  - Sarvenaz Choobdar
AU  - Mehmet E. Ahsen
AU  - Jake Crawford
AU  - Mattia Tomasoni
AU  - David Lamparter
AU  - Junyuan Lin
AU  - Benjamin Hescott
AU  - Xiaozhe Hu
AU  - Johnathan Mercer
AU  - Ted Natoli
AU  - Rajiv Narayan
AU  - The DREAM Module Identification Challenge Consortium
AU  - Aravind Subramanian
AU  - Gustavo Stolovitzky
AU  - Zoltán Kutalik
AU  - Kasper Lage
AU  - Donna K. Slonim
AU  - Julio Saez-Rodriguez
AU  - Lenore J. Cowen
AU  - Sven Bergmann
AU  - Daniel Marbach
TI  - Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases
AID  - 10.1101/265553
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 265553
4099  - http://biorxiv.org/content/early/2018/02/15/265553.short
4100  - http://biorxiv.org/content/early/2018/02/15/265553.full
AB  - Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of networks remains poorly understood. We launched the “Disease Module Identification DREAM Challenge”, an open competition to comprehensively assess module identification methods across diverse gene, protein and signaling networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies (GWAS). While a number of approaches were successful in terms of discovering complementary trait-associated modules, consensus predictions derived from the challenge submissions performed best. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets and correctly prioritize candidate disease genes. This community challenge establishes benchmarks, tools and guidelines for molecular network analysis to study human disease biology (https://synapse.org/modulechallenge).