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

BMC Bioinformatics

Table 5 Evaluation results on software self-extracted features on the QE HF dataset

	TP	FP	TN	FN	P	R	F	F_ACC	A_ACC
MZmine2 RANSAC	6995	11	566	778	0.998	0.900	0.947	0.906	0.721
Local bipartite	7705	6	563	76	0.999	0.990	0.995	0.990	0.975
G-Aligner Greedy	7751	5	563	31	0.999	0.996	0.998	0.996	0.987
G-Aligner Gurobi	7751	5	563	31	0.999	0.996	0.998	0.996	0.987
G-Aligner VLSNS_MSR	7746	5	563	36	0.999	0.995	0.997	0.995	0.986
G-Aligner VLSNS_MSG	7751	5	563	31	0.999	0.996	0.998	0.996	0.987
OpenMS QT	7039	20	1166	125	0.997	0.983	0.990	0.983	0.887
Local bipartite	7092	8	1169	81	0.999	0.989	0.994	0.989	0.972
G-Aligner Greedy	7161	2	1169	18	1.000	0.997	0.999	0.998	0.993
G-Aligner Gurobi	7161	2	1169	18	1.000	0.997	0.999	0.998	0.993
G-Aligner VLSNS_MSR	7161	2	1169	18	1.000	0.997	0.999	0.998	0.993
G-Aligner VLSNS_MSG	7161	2	1169	18	1.000	0.997	0.999	0.998	0.993
XCMS Group	7934	99	134	183	0.988	0.977	0.983	0.966	0.846
XCMS OBI-Warp	7940	70	135	205	0.991	0.975	0.983	0.967	0.846
Local bipartite	8057	36	148	109	0.996	0.987	0.991	0.983	0.938
G-Aligner Greedy	8141	15	148	46	0.998	0.994	0.996	0.993	0.960
G-Aligner Gurobi	8141	15	148	46	0.998	0.994	0.996	0.993	0.960
G-Aligner VLSNS_MSR	8131	20	148	51	0.998	0.994	0.996	0.991	0.957
G-Aligner VLSNS_MSG	8141	15	148	46	0.998	0.994	0.996	0.993	0.960

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

ISSN: 1471-2105