Floranne Boulogne

This paper links common and rare disease genetics by identifying key genes affected by common variants through gene regulatory networks, finding many key genes are outside GWAS loci.

The paper links genes in cancer-susceptibility loci to known somatic driver genes through tissue-specific co-expression networks derived from non-cancer samples.

KidneyNetwork predicts kidney-specific gene functions and disease phenotypes using co-expression networks, identifying ALG6 as a candidate gene for kidney and liver cysts in undiagnosed patients.

The paper integrates DNA methylation and gene expression networks to improve prediction of functional gene-gene associations using eQTMs and a novel integration pipeline.

The paper uses symptom-based case predictions to conduct a GWAS on COVID-19, finding new genetic susceptibility insights and suggesting different genetic architectures for severity and susceptibility.