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GXwasR: A Toolkit for Investigating Sex-Differentiated Genetic Effects on Complex Traits

Bose, B.; Bolstein, F.; Kim, J.; Winters, J.; Actkins, K.; Mayer, D.; Niarchou, M.; Congivaram, H. T. S.; Edwards, D. R. V.; Davis, L.; Stranger, B.

2025-06-11 genetic and genomic medicine
10.1101/2025.06.10.25329327 medRxiv
Show abstract

Many complex traits in humans exhibit sex differences. Recent advances in understanding context-specific genetic effects underscore the imperative for sex-aware genetic analyses to assess the role of sex in the genetic basis of human phenotypes. Despite increasing recognition of the importance of sex as a biological variable, current computational tools for genome-wide association studies (GWAS) lack functionality for performing nuanced sex-aware quality control and analysis. In response, we present GXwasR, a comprehensive R package that implements statistical genetic models for performing both GWAS and X-Chromosome-Wide Association Studies (XWAS). Designed for both sex-combined and sex-stratified analyses, GXwasR can account for unique features of chromosome X, including X-chromosome inactivation. Beyond enabling association analysis and meta-analysis, the tool has functions to a) test for sex differences in SNP-level genetic effects and heritability, b) assess genetic correlation, c) compute sex-aware polygenic risk scores (PRS), and d) support enhanced quality control protocols expressly designed for these purposes. GXwasR thus serves as a computational resource to enable investigations into the role of sex in the genetic basis of complex human phenotypes.

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