Identification of sub-cell types in white blood cells based on clusters generated from single-cell H3K4me3 profiles. (A) A t-SNE visualization of cells by applying the t-SNE analysis on the matrix Ec. Cell type annotations of clusters were obtained by the analysis in part B. (B) A heat map showing the significance of the overlap between the cluster-specific peaks from the H3K4me3 iscChIC-seq data (Fig. 3A) and cell type–specific peaks from ENCODE H3K4me3 ChIP-seq data. The y-axis refers to the cluster-specific peaks and x-axis refers to the cell type–specific peaks. The values before the +/− sign refer to the average negative logarithm of the P-value for the overlap between the two types of peaks over 100 subsamples. The values behind the +/− sign refer to the standard deviation of the negative logarithm of the P-value over 100 subsamples. (C) Genome browser snapshots showing the H3K4me3 profiles from bulk-cell ChIP-seq data and pooled single-cell iscChIC-seq data. The ChIP-seq data for B cells, monocytes, T cells, and NK cells were downloaded from ENCODE (red). The pooled H3K4me3 iscChIC-seq data for each identified cell type (Fig. 3A) are displayed (blue). For the iscChIC-seq data, 1610 monocytes, 1265 T cells, 898 NK cells, and 446 B cells were used. (D) A t-SNE visualization of cells by applying the t-SNE analysis on the matrix Ec. H3K4me3 density of regions associated with different genes is plotted. The color level indicates the H3K4me3 density level.
