MetaSVM

What MetaSVM Is

MetaSVM is a meta-predictor that combines scores from 10 individual pathogenicity prediction tools using a Support Vector Machine (SVM) classifier. Rather than relying on any single tool's assessment, it aggregates signals from multiple methods -- each capturing different aspects of variant impact -- into a single consensus score. This ensemble approach generally produces more reliable predictions than any individual component tool.

Score Interpretation

MetaSVM produces a continuous score. Positive values indicate a predicted damaging effect, negative values indicate a predicted tolerated effect. The further from zero, the higher the confidence.

Strengths and Limitations

As an ensemble method, MetaSVM reduces the bias of individual predictors and generally achieves higher accuracy than any single component tool. It captures multiple dimensions of variant impact simultaneously -- conservation, protein structure, physicochemical properties, and more.

The main limitation is that because MetaSVM combines the same underlying tools used by other predictors, its errors are correlated with them. It is also limited to missense variants and cannot assess splice, nonsense, or non-coding variants.