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. Author manuscript; available in PMC: 2019 Aug 1.
Published in final edited form as: Hum Mutat. 2018 Jun 5;39(8):1061–1069. doi: 10.1002/humu.23553

Table 7.

Validation of semi-quantitative approach for TP53 variant bioinformatic prediction using Align-GVGD class (optimized pMSA) and BayesDel score, using an independent set of non-functional and functional variants

Category Non-functional (n) % Functional (n) % Positive LR (95% CI) LR consistent with proposed ACMG/AMP rule (Table 5)
Optimized Align-GVGD C65 + BayesDel ≥0.16 94 48.45 49 4.32 11.20 (8.22, 15.27) Yes - Moderate evidence of pathogenicity (new rule):18.7≥ Odds Path >4.3
Optimized Align-GVGD C55-C25 + BayesDel ≥0.16 51 26.29 61 5.38 4.88 (3.48, 6.86) Yes - Supporting evidence of pathogenicity (PP3): 4.3≥ Odds Path >2.08
Optimized Align-GVGD C15 + BayesDel ≥0.16 11 5.67 27 2.38 2.38 (1.20, 4.72) No - Not consistent enough with initial results to justify PP3
Optimized Align-GVGD C15 + BayesDel <0.16 1 0.51 42 3.71 0.14 (0.02, 1) Yes - Supporting evidence of benign impact (BP4): 0.23< Odds Path <0.48
Optimized Align-GVGD C0 + BayesDel <0.16 14 7.22 819 72.29 0.10 (0.06, 0.17) Yes - Supporting evidence of benign impact (BP4): 0.23< Odds Path <0.48