GenRisk: a tool for comprehensive genetic risk modeling

Abstract

Summary: The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here, we present GenRisk, a python package for the computation and the integration of gene scores based on the burden of rare deleterious variants and common-variants-based polygenic risk scores. The derived scores can be analyzed within GenRisk to perform association tests or to derive phenotype prediction models by testing multiple classification and regression approaches. GenRisk is compatible with VCF input file formats.

Availability and implementation: GenRisk is an open source publicly available python package that can be downloaded or installed from Github (https://github.com/AldisiRana/GenRisk).

Supplementary information: Supplementary data are available at Bioinformatics online.

Fig. 1.

GenRisk pipeline workflow. A VCF file with functional annotations and frequencies can be used to calculate gene-based scores, alternatively a VCF can be used to extract and calculate PRS. The scores can then be used with phenotypic data for association analysis or to develop prediction models