Supplementary Fig. 8: Single-cell ChIP-seq data distinguish human T cells (Jurkat) from human B cells (Ramos).
From: High-throughput single-cell ChIP-seq identifies heterogeneity of chromatin states in breast cancer
(a) Consensus clustering matrix for H3K4me3 (top panel) and H3K27me3 (bottom panel) scChIP-seq datasets. Consensus score ranges from 0 (white: never clustered together) to 1 (dark blue: always clustered together). (b) Volcano plots representing adjusted P values (two-sided Wilcoxon signed-rank test) versus fold-changes for differential analysis comparing chromatin features between B cells and T cells (thresholds of 0.01 for adjusted P value and 1 for |log2FC|) for H3K4me3 (top panel, n = 1,772 enriched and 926 depleted regions) and H3K27me3 (bottom panel, n = 2,126 enriched and 7,327 depleted regions) scChIP-seq datasets. (c) Barplot displaying the -log10 of adjusted P values from pathway analysis in H3K4me3 scChIP-seq dataset. The top 10 significant gene sets are indicated below the barplot.
