Nomaly

---

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed ‘rare’, even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population). Associative methods give some understanding how rare genetic variants influence disease and organism-level phenotypes. But with Nomaly we show that additional discoveries can be made through a knowledge-based AI approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. Nomaly is an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we can identify plausible novel genetic causes for developmental disorders that  elude other established methods. This system offers a chance to extract further discovery from genetic data after standard tools have been applied.