G-Aligner: a graph-based feature alignment method for untargeted LC–MS-based metabolomics

BMC Bioinformatics

Table 4 Evaluation results on software self-extracted features on the TripleTOF 6600 dataset

	TP	FP	TN	FN	P	R	F	F_ACC	A_ACC
MZmine2 RANSAC	6716	129	422	125	0.981	0.982	0.981	0.966	0.869
Local bipartite	6688	122	413	169	0.982	0.975	0.979	0.961	0.882
G-Aligner Greedy	6847	98	403	44	0.986	0.994	0.990	0.981	0.925
G-Aligner Gurobi	6859	84	403	46	0.988	0.993	0.991	0.982	0.926
G-Aligner VLSNS_MSR	6846	89	403	54	0.987	0.992	0.990	0.981	0.922
G-Aligner VLSNS_MSG	6862	81	403	46	0.988	0.993	0.991	0.983	0.927
OpenMS QT	5771	336	1204	81	0.945	0.986	0.965	0.944	0.741
Local bipartite	5355	338	1248	451	0.941	0.922	0.931	0.893	0.697
G-Aligner Greedy	5922	140	1230	100	0.977	0.983	0.980	0.968	0.874
G-Aligner Gurobi	5910	152	1233	97	0.975	0.984	0.979	0.966	0.876
G-Aligner VLSNS_MSR	5906	156	1233	97	0.974	0.984	0.979	0.966	0.873
G-Aligner VLSNS_MSG	5910	152	1233	97	0.975	0.984	0.979	0.966	0.876
XCMS Group	6567	251	38	536	0.963	0.925	0.943	0.894	0.712
XCMS OBI-Warp	6173	293	39	887	0.955	0.874	0.913	0.840	0.600
Local bipartite	6939	152	51	250	0.979	0.965	0.972	0.946	0.866
G-Aligner Greedy	7281	52	47	12	0.993	0.998	0.996	0.991	0.956
G-Aligner Gurobi	7283	47	47	15	0.994	0.998	0.996	0.992	0.957
G-Aligner VLSNS_MSR	7270	51	47	24	0.993	0.997	0.995	0.990	0.951
G-Aligner VLSNS_MSG	7283	47	47	15	0.994	0.998	0.996	0.992	0.957

The results with the highest performance in the comparison are indicated in bold

ISSN: 1471-2105