# XPRS: a tool for interpretable and explainable polygenic risk score

## TL;DR

XPRS is a new tool that makes polygenic risk scores more interpretable by showing which genes and SNPs contribute most to an individual's genetic risk for diseases.

## Contribution

XPRS introduces a novel visualization and interpretation framework for PRS using SHAP values to highlight key genetic contributors.

## Key findings

- XPRS uses SHAP values to break down PRS into gene and SNP contributions.
- The tool provides multilevel visualizations like Manhattan and LocusZoom plots for better interpretation.
- XPRS is available as a web-based tool to improve clinical communication and understanding of genetic risk.

## Abstract

The polygenic risk score (PRS) is an important method for assessing genetic susceptibility to diseases; however, its clinical utility is limited by a lack of interpretability tools. To address this problem, we introduce eXplainable PRS (XPRS), an interpretation and visualization tool that decomposes PRSs into genes/regions and single nucleotide polymorphism (SNP) contribution scores via Shapley additive explanations (SHAPs), which provide insights into specific genes and SNPs that significantly contribute to the PRS of an individual. This software features a multilevel visualization approach, including Manhattan plots, LocusZoom-like plots, and tables at the population and individual levels, to highlight important genes and SNPs. By implementing with a user-friendly web interface, XPRS allows for straightforward data input and interpretation. By bridging the gap between complex genetic data and actionable clinical insights, XPRS can improve communication between clinicians and patients.

The XPRS software is publicly available on GitHub at https://github.com/nayeonkim93/XPRS and can see the demo through our cloud-based web service at https://xprs.leelabsg.org/.