An AI-Assisted Comparative GWAS Pipeline Identifies Candidate Sex-Biased Schizophrenia Loci near CYP26B1 and EXOC6B

Large genome-wide association studies (GWASs) have generated extensive summary-statistics resources across psychiatric disorders, ancestries, and sex strata. These resources create an opportunity to compare genetic architectures across related datasets, but practical tools for identifying both shared and divergent association signals remain limited. We developed an AI-assisted workflow for local comparative analysis and visualization of multiple psychiatric GWAS summary-statistics datasets. The workflow harmonizes input GWASs, computes pairwise differential association statistics, prioritizes shared loci with concordant evidence across paired datasets, and renders genome-wide and locus-level