Figure 2

Figure 2

Segmentation of accessibility profiles reveals cell-type-specific and shared regulatory regions

(A) Schematic representation of ScregSeg for identifying regulatory programs (ScregSeg-pi). The genome is divided into 500-bp bins and segmented based on the accessibility distribution over the cluster-collapsed accessibility tracks using a 30-state HMM. The bins are assigned to states that give rise to the classification of the regulatory landscape of the genome.

(B) Heatmap representing the association between states and clusters based on the log-ratio between the states’ emission probabilities and the (normalized) overall read coverage per cluster, which accounts for read depth per cluster (see STAR Methods). Display restricted to states showing the strongest association with single-cell-type clusters (left) and multiple-cell-type clusters (right; full heatmap in Figure S2A). ScregSeg-pi states 5 and 18 (highlighted) encompass CREs accessible in 4 neuronal cell-type clusters. Accessibility of 100 CREs with the highest assignment probability for these states represented in UMAP space, in which the color represents the rank-based AUCell enrichment score for a given region.^35,36 Loci around ascl1b have a high probability of assignment to states 5 and 18, as indicated below the cluster-aggregated accessibility tracks, and the ascl1b locus (highlighted in pink) shows a high normalized enrichment in the UMAP territory representing neuronal cell types.

(C) Two examples of a cell-type cluster (tail bud and midbrain) that are associated with multiple ScregSeg-pi states (26, 25, and 13 and 5 and 24, respectively). The right-hand panel shows the per-cell distribution of accessibility at the gene body of genes mapping to segments, with the top 100 logFC enrichments for each of these states.