established methods for a scaled PhIP-seq protocol that can test 800 samples in parallel and used them to generate large datasets of antigens for APS1, IPEX, RAG1/2 deficiency, Kawasaki disease, multisystem inflammatory syndrome in children, and mild and severe forms of COVID-19 and employed machine learning to construct models that can predict disease status and individual antigens that could serve as biomarkers for these diseases. The gene discussed is RAG1; the disease is Kawasaki disease.