Fig. 9
From: Using multi-scale genomics to associate poorly annotated genes with rare diseases
EvORanker outperforms two other algorithms (ExomeWalker and PHIVE). The performance of each algorithm in the 108-exome dataset and the simulated dataset (shuffled three times) was measured by examining the ranking of the “true” disease-causing gene relative to the other patient genes. The upper bar plot shows results for the autosomal and X-linked recessive cases for the real-exome dataset (left) and the simulated dataset (right). The simulated dataset contains 181 unique recessive cases and 119 unique dominant cases. The results present a compilation of three separate independent shuffles totaling 900 simulations. The lower bar plot shows results for the autosomal and X-linked dominant cases. The y-axis indicates the tested algorithms, and the x-axis indicates the percentage of cases where the “true” disease gene was ranked at the top or within the top 5 genes relative to the other candidate genes in recessive cases. In dominant cases, the percentage indicates whether the “true” gene was ranked at the top or within the top 10 genes. EvORanker outperformed ExomeWalker and PHIVE in both recessive and dominant diseases in both datasets