In this repository, we evaluate six network-based GWAS tools on the GENESIS dataset. It containts the accompanying scripts, results, and laboratory notebooks of the following article:

Climente-González H, Lonjou C, Lesueur F, GENESIS study group, Stoppa-Lyonnet D, et al. (2021) Boosting GWAS using biological networks: A study on susceptibility to familial breast cancer. PLOS Computational Biology 17(3): e1008819. https://doi.org/10.1371/journal.pcbi.1008819

This repository is organized into four main subfolders:

• scripts/: contains the mai pieces code using to run the experiments.
• results/: contains the results of the experiments. Generally, every subfolder contains a script run.sh which, upon running, produced all the files within that directory.
• doc/: contains the Jupyter notebooks in which the results are analyzed (see below).

Analyses

• Conventional GWAS, including SNP- and gene-level summary statistics.
• Recovering known biomarkers
• Method benchmark
• SConES results
• Consensus network
• Stable consensus
• Genes excluded from the analysis

Manuscript

• Manuscript
• Figures
• Supplementary figures