Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase

Table 1 Accuracy Indexes

Category	Predictor	Raw Accuracy	Balanced accuracy	F1-score	Matthew’s correlation coefficient
B	SIFT	0.749	0.549	0.241	0.092
B	LRT	0.794	0.576	0.280	0.162
B	MutationAssessor	0.191	0.460	0.247	−0.106
B	FATHMM	0.846	0.500	0.000	0.000
B	PROVEAN	0.737	0.557	0.258	0.103
Meta	MetaSVM	0.846	0.500	0.000	0.000
Meta	MetaLR	0.846	0.500	0.000	0.000
Meta	M-CAP	0.846	0.500	0.000	0.000
ML	Polyphen2_HDIV	0.771	0.592	0.310	0.175
ML	Polyphen2_HVAR	0.691	0.621	0.341	0.188
ML	MutationTaster	0.194	0.433	0.230	−0.156
ML	FATHMM-MKL	0.829	0.505	0.063	0.022

Accuracy indexes measuring the ability to differentiate severe from mild GLA mutations for all the predictors used by wANNOVAR. Categories are B for “biologically based prediction method”, ML for “Machine Learning based prediction method”, and Meta for “Meta prediction method”

ISSN: 1471-2105