LocusPackRat: An R Package to Support Prioritizing Candidate Genes from Large GWAS Intervals with Standardized Evidence Aggregation

Genome-wide association studies (GWAS) routinely implicate broad loci that span tens of megabases and contain dozens of genes, making the leap from locus to causal gene challenging, especially in model organism cohorts with reduced mapping resolution. We developed LocusPackRat, an easily extendable R package that assembles standardized 'packets' of evidence to accelerate candidate gene prioritization. Each packet merges study-specific information for each gene in a locus such as differential expression between conditions or presence of cis-eQTLs with functional/disease annotations pulled from InterMine and Open Targets. Packets are identically structured and easily disseminated to support side-by-side comparison and team review. We demonstrate LocusPackRat's efficacy on a recent GWAS study of cardiac hypertrophy and failure in the Collaborative Cross. LocusPackRat streamlines the transition from statistical associations to mechanistic hypotheses by providing a systematic, transparent framework for GWAS data integration, and is readily adaptable to other genetic reference populations or human cohorts.