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Fig. 1 | Genome Medicine

Fig. 1

From: Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases

Fig. 1

The diagnostic sensitivity of GEM was greater than the variant prioritization methods Phevor, Exomiser, and VAAST. A Proportion of the benchmark cohort of 119 cases where the true causal genes (or variants in the case of causal SVs) were identified among the top 1st, 2nd, 5th, or 10th gene candidates. Patient phenotypes were extracted manually from medical records by clinicians and provided as HPO term inputs to GEM, Exomiser, and Phevor. VAAST only considers variant information. It should be noted that GEM and Phevor ranks correspond to genes, which may include one or two variants (the latter in the case of a compound heterozygote), whereas Exomiser and VAAST ranks were for single variants. In the case of compound heterozygotes, the rank of the top-ranking variant is shown for Exomiser and VAAST. B Comparison of GEM performance in the validation cohort (excluding SV cases) versus the validation cohort (comprised of 60 rare genetic disease cases from multiple sources)

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