Fig. 5: Dominant-negative and gain-of-function mutations are less well identified by nearly all computational variant effect predictors than loss-of-function mutations. | Nature Communications

Fig. 5: Dominant-negative and gain-of-function mutations are less well identified by nearly all computational variant effect predictors than loss-of-function mutations.

From: Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure

Fig. 5

AUC values calculated from ROC curves for discriminating between different types of pathogenic ClinVar mutations and putatively benign gnomAD variants, using the outputs of different computational variant effect predictors. Only homozygous gnomAD variants were included for the AR analysis. Error bars denote 95% confidence intervals. Source data are provided as a Source Data file.

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