Fig. 6. Clustering analysis on the human liver cells with marker gene-based constraints.

a Clustering performances of PhenoGraph and k-means on ZIFA representations of marker genes, SC3, and scDCC (with and without constraints) on mRNAs of the human liver dataset measured by NMI, CA, and ARI. All experiments are repeated ten times (one dot represents one experiment), and the means and standard errors are displayed. Constraints were constructed by marker genes. b Average (with constraints comparing to without constraints) of specificity scores of 55 marker genes. One-sided Wilcoxon test p-value is also displayed (with constraints vs. without constraints). c Marker gene expression (log normalized counts) for each cell marked on the t-SNE plot based on latent representations of scDCC without any constraint. d Marker gene expression (log normalized counts) for each cell marked on the t-SNE plot based on latent representations of scDCC with 25,000 pairwise constraints. c, d t-SNE plots calculated from the bottleneck features of scDCC with and without constraints, respectively. Colors represent the relative expression levels; gray and red represent low and high expression levels, respectively. Axes are arbitrary values.