Fig. 3: Bioinformatic tools for predicting abnormal splicing. | Genetics in Medicine

Fig. 3: Bioinformatic tools for predicting abnormal splicing.

From: Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance

Fig. 3: Bioinformatic tools for predicting abnormal splicing.

Receiver operating characteristic (ROC) curves and area under the curve (AUC) comparing in silico methods for predicting splice disruption in overlapping set of experimentally validated variants scored by all measures (136 non–splice disrupting, 70 splice disrupting). HSF human splicing finder, MES MaxEntScan (Alamut), NN NNSplice (Alamut), SSF SpliceSiteFinder (Alamut). Ala23 = number of Alamut tools exceeding specified thresholds.

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