Table 3.

Silhoutte scores comparison of proposed method with other dimensionality reduction techniques.

Dataset name	t-SNE	PCA	Isomap	Standard LLE	Eigenmaps	MLLE	MLLE+ICA
Baron_human1	0.244	0.364	0.498	0.524	0.839	0.908	0.904
Baron_human2	0.231	0.428	0.543	0.614	0.823	0.906	0.905
Baron_human3	0.243	0.377	0.522	0.467	0.826	0.990	0.976
Baron_human4	0.239	0.424	0.614	0.538	0.896	0.910	0.912
Baron_mouse1	0.231	0.400	0.422	0.448	0.472	0.881	0.917
Baron_mouse2	0.221	0.414	0.530	0.684	0.779	0.941	0.943
Muraro	0.258	0.494	0.532	0.738	0.913	0.933	0.944
Segerstolpe	0.231	0.410	0.399	0.400	0.537	0.960	0.956
Xin	0.242	0.445	0.481	0.494	0.751	0.899	0.888
Wang	0.230	0.484	0.442	0.745	0.608	0.993	0.996
H1299 scRNA-seq	0.245	0.269	0.701	0.683	0.782	0.938	0.943
Calu3 scRNA-seq	0.361	0.232	0.494	0.452	0.798	0.889	0.924
PBMC	0.244	0.401	0.622	0.621	0.632	0.867	0.876

Significant values are in bold.