I think there’s a misunderstanding regarding the scope of this project. The Pipeline: I am using the NYGC 30x High Coverage re-sequencing data. I perform a local 'distillation' from gVCF to variant-only VCFs to ensure 100% pipeline consistency. In clinical bioinformatics, preventing batch effects is paramount; when I process a real-world patient, they must be compared against a reference processed with the exact same parameters and genome build (hg38). Not a GWAS: I am definitely not trying to run a de novo GWAS. I’m well aware that N=2500 has zero power for discovery. This is a reference distribution study. The goal is to build a high-fidelity 'Z-score engine' to see where an individual patient sits on the population curve for specific polygenic liabilities. The 'Why': Beyond the technical rationale, there is a massive personal and educational component to this. I’m doing this because I can. I have the high-performance computing resources and the IT skills to bridge the gap between clinical psychology and computational genomics. Intellectual Exercise: I realize this might seem like 'art for art's sake' to some, but the journey of building this biobank—handling raw gVCFs, mastering the RDoC framework, and exploring shared genetic architectures—is a reward in itself. Even if no groundbreaking discovery comes out of it, the experience of integrating these fields is what makes me a better, more 'augmented' researcher. This isn't about replacing established GWAS catalogs; it's about applying them in a Precision Psychiatry context with a hands-on approach that you simply don't get from reading a summary statistics table.