For the second year in a row, our hereditary disease solution for exomes, genomes, and large panels was the most accurate in the CAGI Hopkins challenge.
Dr. Sohela Shah, Principal Genome Scientist of Advanced Clinical Testing at QIAGEN Bioinformatics, was one of four presenters to discuss her approach to the challenge. Each participant had to assign patients to the correct clinical phenotype based on variant calls for 83 genes from a cohort of 106 patients with a range of clinical presentations. Our solution identified 43 disease-causing variants, outperforming other models.
CAGI offers a chance for the genomics community to objectively assess computational methods that predict phenotypic impacts of genomic variation, based solely on analysis of gene panel variant data. The predictions are evaluated against experimental characterizations by independent assessors.
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