Phevor integrates phenotype, gene function, and disease information with personal genomic data for improved power to identify disease-causing alleles. Phevor works by combining knowledge resident in multiple biomedical ontologies with the outputs of variant prioritization tools. It does so using an algorithm that propagates information across and between ontologies. This process enables Phevor to accurately re-prioritize potentially damaging alleles identified by variant prioritization tools in light of gene function, disease, and phenotype knowledge.
Phevor is especially useful for single exome and family trio-based diagnostic analyses, the most commonly occurring clinical scenarios, and ones for which existing personal-genomes diagnostic tools are most inaccurate and underpowered.
Importantly, Phevor is not limited to known diseases, or known disease-causing alleles. Phevor can also use latent information in ontologies to discover genes and disease causing-alleles not previously associated with disease.
Phevor Combines Multiple Biomedical Ontologies for Accurate Identification of Disease-Causing Alleles in Single Individuals and Small Nuclear Families. Am J Hum Genet. 2014 Apr 3;94(4):599-610
• A Disease-Gene Association for NFKB2 - Two families were affected by autosomal-dominant, early-onset hypogammaglobulinemia with variable auto- immune features and adrenal insufficiency. Four individuals from family A were sequenced, and the affected individual in family B was sequenced. Two different NFKB2 mutations were identified (different ones in family A and B)., and was the top ranked candidate from the combined VAAST and Phevor analysis. NFKB2 is a gene that had previously not been identified to be associated with this disease.
This case demonstrates Phevor’s ability to identify a human gene not currently associated with a disease or phenotype in the Human Phenotype Ontology, Disease Ontology, or Mammalian Phenotype Ontology.
• An Atypical Phenotype Caused by a Dominant Allele of STAT1 - The patient was a 12 year-old male with severe diarrhea in the context of intestinal inflammation, total villous atrophy, and hypothyroidism. His clinical picture was life threatening, warranting hematopoietic stem cell transplantation despite diagnostic uncertainty. He was diagnosed with diagnosis of X-linked immunodysregulation, polyendocrinopathy, and enteropathy, but targeted sequencing of genes associated with these conditions revealed no pathogenic variants. Exome sequencing was conducted for the patient and both parents. A combined VAAST-Phevor analysis ranked a STAT1 de novo mutation as the top disease-causing candidate.
These results highlight Phevor’s ability to use only a single affected exome to identify a mutation located in a known disease-associated gene and producing an atypical phenotype.