This study evaluates trait selection strategies in multi-trait GWAS, finding that diverse trait sets improve variant detection compared to univariate screening and specific methods like JASS outperform others.

Human Genetics and Genomics Advances · Jun 13, 2024Peer-reviewedGenetics

HARIBOSS: a curated database of RNA-small molecules structures to aid rational drug design

Francesco Paolo Panei, Rachel Torchet, Hervé Ménager, Paraskevi Gkeka, Massimiliano Bonomi

HARIBOSS is a curated database of RNA-small molecule structures to support rational drug design by providing insights into RNA-ligand interactions.

Bioinformatics · Jul 7, 2022Peer-reviewedBioinformatics

Multitrait genetic-phenotype associations to connect disease variants and biological mechanisms

Hanna Julienne, Vincent Laville, Zachary Ryan McCaw, Zihuai He, Vincent Guillemot, Carla Lasry, Andrey Ziyatdinov, Amaury Vaysse, Pierre Lechat, Hervé Ménager, Wilfried Le Goff, Marie‐Pierre Dubé, Peter Kraft, Iuliana Ionita‐Laza, Bjarni Jóhann Vilhjálmsson, Hugues Aschard

The paper decomposes multitrait genetic associations to identify pleiotropy profiles linking SNPs to biological pathways and drug targets.

bioRxiv · Jun 26, 2020 · PreprintGenetics

JASS: Command Line and Web interface for the joint analysis of GWAS results

Hanna Julienne, Pierre Lechat, Vincent Guillemot, Carla Lasry, Chunzi Yao, Robinson Araud, Vincent Laville, Bjarni Jóhann Vilhjálmsson, Hervé Ménager, Hugues Aschard

JASS is a Python package that enables joint analysis of GWAS summary statistics to detect new genetic variants, with a web interface and efficient algorithms for large-scale analysis.

NAR Genomics and Bioinformatics · Jan 24, 2020Peer-reviewedBioinformatics