A network-guided protocol to discover susceptibility genes in genome-wide association studies using stability selection

Héctor Climente-González; Chloé-Agathe Azencott; Makoto Yamada

doi:10.1016/j.xpro.2022.101998

A network-guided protocol to discover susceptibility genes in genome-wide association studies using stability selection

STAR Protoc. 2023 Mar 17;4(1):101998. doi: 10.1016/j.xpro.2022.101998. Epub 2023 Jan 6.

Authors

Héctor Climente-González¹, Chloé-Agathe Azencott², Makoto Yamada³

Affiliations

¹ RIKEN Center for Advanced Intelligence Project, Chuo-ku, Tokyo 103-0027, Japan. Electronic address: hector.climente@riken.jp.
² Centre for Computational Biology (CBIO), MINES ParisTech, PSL Research University, 75005 Paris, France; Institut Curie, PSL Research University, 75005 Paris, France; INSERM, U900, 75005 Paris, France.
³ RIKEN Center for Advanced Intelligence Project, Chuo-ku, Tokyo 103-0027, Japan; Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan; Machine Learning and Data Science Unit, Okinawa Institute of Science and Technology Graduate University, Onna-son, Okinawa 904-0495, Japan.

Abstract

We present a network-based protocol to discover susceptibility genes in case-control genome-wide association studies (GWASs). In short, this protocol looks for biomarkers that are informative of disease status and interconnected in an underlying biological network. This boosts discovery and interpretability. Moreover, the protocol tackles the instability of network methods, producing a stable set of genes most likely to replicate in external cohorts. To apply the procedure to a provided GWAS dataset, install the required software and execute our command-line tool. For complete details on the use and execution of this protocol, please refer to Climente-González et al.¹.

Keywords: Bioinformatics; Genetics; Genomics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Genome-Wide Association Study* / methods
Software*