Table 3.

The performance of prediction methods using the missense variants

Order	Methods	Accuracy	Precision	Recall	F1-score
1	PredictSNP2	0.6983	0.7042	0.7609	0.7315
2	DANN	0.6716	0.6642	0.7928	0.7228
3	FATHMM-MKL	0.6793	0.6884	0.7422	0.7143
4	FunSeq2	0.5947	0.6046	0.7211	0.6577
5	CADD	0.7198	0.7453	0.7312	0.7382
6	SIFT	0.7146	0.7771	0.6612	0.7145
7	PROVEAN	0.7267	0.7476	0.7457	0.7467
8	MetaLR	0.7964	0.8360	0.7751	0.8044
9	MetaSVM	0.8015	0.8409	0.7802	0.8094
10	MutationAssessor	0.7163	0.7797	0.6617	0.7159
11	PrimateAI	0.6877	0.6939	0.7546	0.7230
12	M-CAP	0.8040	0.8494	0.7744	0.8101
13	REVEL	0.8305	0.8578	0.8226	0.8398
14	MISTIC	0.8216	0.8604	0.7994	0.8288