Figure 3From: Cell-type specificity of ChIP-predicted transcription factor binding sitesHigher peaks overlap more and have more consistent support in other data marking regulatory regions. Peaks in K562 for each TF (panel columns) were binned in 10 equally-sized groups with increasing peak height (ordered along x-axis) and the average values for different genomic characteristics (panel rows) were computed for each group (y-axis). From top to bottom row, the genomic characteristics are: “HeLa-S3”: percentage of peaks in K562 that overlap with a peak in HeLa-S3.; “Promoter”: percentage of peaks that overlap with promoter regions.; “CpG rich”: percentage of peaks that overlap with CpG-rich regions.; “DNase”: average count of DNase-seq reads in peak region—a measure of chromatin accessibility.; “H3K4me3”: average count of H3K4me3 ChIP-seq reads in a peak region—a measure of chromatin activity.; “phyloP”: average phyloP scores in peak region for a 28-way placental mammals multiple alignment—a measure of sequence conservation.; “PWMscore”: average maximal PWM score in peak region (where available).; “ClusterTF”: average number of peaks in peak cluster. See Methods section for definition of promoters, CpG-rich regions, and clusters and for details on other genomic data. The blue line in each panel is a linear regression line between peak height bin and genomic characteristic; the dark gray areas surrounding these lines are 95% confidence intervals; blue stars mark significant regression line slopes (p ≤0.05).Back to article page