Findings from the Critical Assessment of Genome Interpretation, a community experiment to evaluate phenotype prediction. S. E. Brenner1, J. Moult2, CAGI Participants 1) University of California, Berkeley, CA; 2) IBBR, University of Maryland, Rockville, MD.

   The Critical Assessment of Genome Interpretation (CAGI, 'kā-jē) is a community experiment to objectively assess computational methods for predicting the phenotypic impacts of genomic variation. In the experiment, participants are provided genetic variants and make predictions of resulting phenotype, for ten challenges. These predictions are evaluated against experimental characterizations by independent assessors.
    For example, in a challenge to predict Crohns disease from exomes, several groups performed remarkably well, with one group achieving a ROC AUC of 0.94. The experiment also revealed important population structure to Crohns disease in Germany. In another challenge, two groups were able to successfully map a significant number of Personal Genome Project complete genomes to corresponding trait profiles.
   Other challenges were to predict which variants of BRCA1, BRCA2, and the MRN complex are associated with increased risk of breast cancer; to associate exomes, variants, and disease in lipid diseases; to predict how variants in p53 gene exons affect mRNA splicing; to predict how well variants of p16 tumor suppressor protein inhibit cell proliferation; and to identify potential causative SNPs in disease-associated loci.
    Overall, CAGI revealed that the phenotype prediction methods embody a rich representation of biological knowledge, making statistically significant predictions. However, the accuracy of prediction on the phenotypic impact of any specific variant was unsatisfactory and of questionable clinical utility. The most effective predictions came from methods honed to the precise challenge. Prediction methods are clearly growing in sophistication, yet there are extensive opportunities for further progress.
   Complete information about CAGI may be found at

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