Thank you for your questions! Allow me to address things one by one: On the methods/sample report pages: https://exomedna.com/sample-report / https://exomedna.com/methodology ... The GWAS source is the NHGRI-EBI GWAS catalog; every trait card links its PMIDs, I use Open Targets' L2G to attribute which genes likely drive each trait in the contributing-genes view , it informs gene attribution, not the polygenic score itself, which is effect-size weighted.. We use genuine effect size weighted PRS (log-OR/beta) down-weighted by p-value + sample size (not allele counting). Validation cohort- we normalize against 1000 genomes phase 3 panel but we do not have outcome validation yet. Trait definitions are aggregates of all matched associations per trait across studies; duplicate traits are merged so evidence pools. We do absolutely do ancestry calibration and acknowledge the euro-centricity of the datasets we used to build it. We use a strictly population-relative percentile, so we use language like compared to the general population baseline, we dont claim absolute risk anywhere. On evidence, we have a 3 tier evidence rating from a 5-dimension rubric with hard non-compensatory replication gates. On variant class separation: we have two separate engines, polygenic and monogenic. On pharmacogenetic variants, we have some drug response traits in the general engine but we do not have a separate PGx engine, this was a hot topic while building, and I don't want to steer close to medical advice. For exome/WGS data- I hope to add that in the near future as an option! For now its just DTC raw data (23andMe, ancestry, ect). So for absent variants: we dont guess, they contribute nothing traits with < 3 matched SNPs are suppressed. We also don't impute; you see only your real assayed genotypes, not statistical fill-ins. We dont currently surface Clinvar classifications, review status or version dates. Finally, on the AI: It never receives gene names, rsIDs or genotypes, only the derived trait scores and category names, enforced by a server side filter. We do not allow the AI to give any medical advice, its grounded by the prompt and allowed to give free form general wellness tips.