Table 2.

Performance comparison of CNDM and NDM in clustering of scRNA-seq data

Method	Input	Buettner[15]	Kim[43]	Wang[45]	Gokce[46]	Tabula Muris[47](aorta)	Tabula Muris[47](limb muscle)
K-means	NDM	0.50	0.50	0.30	0.79	0.21	0.58
	CNDM	0.87	0.81	0.45	0.75	0.63	0.66
Hierarchical	NDM	0.69	0.59	0.38	0.95	0.12	0.65
	CNDM	0.73	0.77	0.45	0.92	0.75	0.76
K-means (t-SNE)	NDM	0.83	0.84	0.61	0.38	0.46	0.62
	CNDM	0.95	0.93	0.67	0.36	0.61	0.65
Hierarchical (t-SNE)	NDM	0.89	0.98	0.58	0.47	0.50	0.66
	CNDM	0.95	0.95	0.72	0.39	0.50	0.66
K-medoids	NDM	0.26	0.49	0.31	0.60	0.35	0.14
	CNDM	0.53	0.61	0.21	0.81	0.53	0.39
SC3	NDM	0.67	1	0.70	0.45	0.29	0.66
	CNDM	0.98	0.96	0.86	0.72	0.73	0.76
SIMLR	NDM	0.64	0.75	0.29	0.74	0.40	0.60
	CNDM	0.63	0.95	0.60	0.85	0.70	0.71
Seurat	NDM	0.82	0.97	0.59	0.44	0.45	0.66
	CNDM	0.90	0.84	0.59	0.32	0.76	0.75

Note: The performance of clustering is evaluated by ARI. Hierarchical (t-SNE) and K-means (t-SNE) indicate clustering after t-SNE. NDM, network degree matrix. Bold font (ARI) indicates that CNDM performs better.