Fig. 2

Performance of in silico prediction tools as stand-alone methods or in combination. Sensitivity (SENS), specificity (SPEC), accuracy (ACC) and Matthews correlation coefficient (MCC) of stand-alone tools and combinations of prediction tools Align-GVGD, SIFT, MutationTaster2 (MT) and PolyPhen-2 (PPhen-2) as observed and estimated from the sensitivities and specificities of stand-alone methods on the Evaluation Variant Set of 166 missense variants on BRCA1 and BRCA2. Align-GVGD, SIFT and MutationTaster2 reached values for sensitivity > 0.92 as stand-alone tools as well as in combination. The comparatively low sensitivity of PolyPhen-2 as a stand-alone approach is also reflected in the decreased sensitivities of combined approaches involving PolyPhen-2. The specificities of stand-alone tools varied between 0.67 (PolyPhen-2) and 0.92 (Align-GVGD), and the specificities of combined approaches increased with increasing m. False negatives (false positives, respectively) denote the number of index patients tested in GC-HBOC as of September 2016 that would receive an erroneous negative (respectively positive) result if the diagnosis were based solely on the corresponding in silico approach