GenRisk: a tool for comprehensive genetic risk modeling

• DOI: 10.1093/bioinformatics/btac152
• Publication Date: 2022-03-09T20:11:57Z
• Authors: Rana Aldisi; Emadeldin Hassanin; Sugirthan Sivalingam; Andreas Buness; Hannah Klinkhammer; Andreas Mayr; Holger Fröhlich; Peter Krawitz; Carlo Maj
• Keywords: Python; R package; Genetic architecture

The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious in coding regions larger sizes. However, the two kinds contributions are typically analyzed independently. Here, we present GenRisk, a python package for computation integration gene scores based on burden common-variants-based polygenic risk scores. derived within GenRisk to perform association tests or derive phenotype prediction models testing multiple classification regression approaches. is compatible VCF input file formats.GenRisk an open source publicly available that downloaded installed from Github (https://github.com/AldisiRana/GenRisk).Supplementary data at Bioinformatics online.