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Fig. 5 | Genome Medicine

Fig. 5

From: Gain and loss of TASK3 channel function and its regulation by novel variation cause KCNK9 imprinting syndrome

Fig. 5

Combining experimental and computational approaches adds mechanistic detail to interpreting genetic variants. A Most DNA sequence-based algorithm predicts our cohort’s variants uniformly, but there is a stark lack of consensus among them. Each genomic score was thresholded according to how we used them to the ACMG classification PP3 criteria. B Our experiments clarified specific functional changes for each mutated protein, resulting in an in vivo impact class and C updating the ACMG classification of each variant. D Computational assays were additionally summarized and demonstrated variant-specific changes to key regions of the protein and resulting in a predicted impact class (further detail in Additional file 2: Table S1). E The impact classes from experimental and computational approaches were highly concordant, demonstrating the potential for computational tools to enhance the information available for interpreting genetic variants. We summarized concordance using a bubble plot with radius proportional to the number of variants in each class. Variants are colored according to their ACMG Class, and bubbles are colored according to Impact Class (left side computational and right in vitro)

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