A heritability-optimized method for functional prioritization of rare coding variants in complex traits

RovHer's heritability‑optimized scoring method for rare coding variants, demonstrated on the UK Biobank to enrich missense rare variants that maximally explain complex traits, marks a breakthrough in functional genomics that will soon be embedded in AI‑driven variant‑interpretation platforms. For website owners running biomedical databases, research portals, or health‑tech blogs, this development means a surge of specialized AI bots that will scrape gene‑variant data, model heritability scores, and feed training pipelines for predictive health tools. These bots often generate high‑frequency requests to variant‑lookup APIs and may inadvertently overload servers or extract proprietary datasets, raising both performance and compliance concerns. **Actionable steps:** 1. **Update your llms.txt** to explicitly list “RovHer”, “heritability‑optimized scoring”, and related endpoints (e.g., `/api/variant`, `/data/ukb`) as disallowed for generic crawlers while permitting vetted research bots via a token‑based whitelist. 2. **Implement bot‑traffic monitoring** with custom signatures for requests containing parameters like `rsID`, `missense_score`, or `heritability_weight`; flag spikes and throttle IPs that exceed baseline thresholds. 3. **Deploy a verification layer** that requires API keys for any access to rare‑variant datasets, ensuring that only authorized AI services can retrieve the high‑value functional scores generated by RovHer.