A computational approach for detecting physiological homogeneity in the midst of genetic heterogeneity

The human genetic dissection of clinical phenotypes is complicated by genetic heterogeneity. Gene burden approaches that detect genetic signals in case-control studies are underpowered in genetically heterogeneous cohorts. We therefore developed a genome-wide computational method, network-based heterogeneity clustering (NHC), to detect physiological homogeneity in the midst of genetic heterogeneity. Simulation studies showed our method to be capable of systematically converging genes in biological proximity on the background biological interaction network, and capturing gene clusters harboring presumably deleterious variants, in an efficient and unbiased manner.

Source: The American Journal of Human Genetics - May 19, 2021 Category: Genetics & Stem Cells Authors: Peng Zhang, Aur élie Cobat, Yoon-Seung Lee, Yiming Wu, Cigdem Sevim Bayrak, Clémentine Boccon-Gibod, Daniela Matuozzo, Lazaro Lorenzo, Aayushee Jain, Soraya Boucherit, Louis Vallée, Burkhard Stüve, Stéphane Chabrier, Jean-Laurent Casanova, Laurent Ab Tags: Article Source Type: research