Our hereditary disease solution performs best in terms of clinical accuracy at the Critical Assessment of Genome Interpretation (CAGI) conference.
For the second year in a row, our hereditary disease solution for exomes, genomes, and large panels performed best in terms of accuracy among all the participants of the CAGI conference and was promoted as such during the meeting.
CAGI offers a chance for the genomics community to objectively assess computational methods that predict phenotypic impacts of genomic variation and to inform future research directions. In the Hopkins clinical panel challenge, participants should use computational methods to predict a patient’s clinical phenotype and the causal variant(s) based solely on analysis of their gene panel variant data. The predictions are evaluated against experimental characterizations by independent assessors, and the CAGI experiment ends every year with a community workshop and publications to disseminate results.
This year at CAGI 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 was provided variant calls for 83 genes from a cohort of 106 patients with a range of clinical presentations and had to align the patients to the correct clinical phenotype. As presented by Sohela, our solution performed best in terms of clinical accuracy.
More information about the hereditary disease solution
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