a Schematic of the regulatory potential (RP) model. The regulatory effect of TF i on gene j is modeled as the RP, Ri, j(Δ), which sums up all TF i ChIP-seq binding effects on the gene j. The effect of a single binding site k of TF i on gene j decays exponentially with increasing , the genomic distance between TSS of gene and TF binding site . The exponential decay function () is parameterized by the decay distance (Δ), the distance at which the TF regulatory effects are halved. b TF -specific regulatory decay distances () can be inferred as the Δ that best separates TF perturbation-induced differentially expressed (DE) genes from other genes. with short-range (<1 kb) best separates FOXM1-knockdown or GABPA-knockdown DE gene sets (left). AR overexpression or ESR1-knockdown DE gene sets are best separated by with long-range Δ (>10 kb). The two-sided Kolmogorov–Smirnov two-sample test is used to estimate the degree of separation of DE genes from other genes. c
can also be inferred as the that leads to the best concordance between TF regulatory effects estimated by TF ChIP-seq () and expression cohorts (: TF i-gene expression correlations), respectively. A second correlation coefficient was calculated to measure the concordance between and (see the main text for the rationale and Methods for statistical details). d TFs with short-range (100bp-3 kb) include YY1, CREB1, FOXM1, ATF1, and TFDP1 (left). TFs with long-range (3 kb–100 kb) include PPARG, FOXA1, GRHL2, FOSL2, and TEAD1 (right). Colored shaded regions depict the 95% confidence intervals derived from all ChIP-seq samples that passed QC for each TF. Dots along the line are Δ values being tried. e Distribution of regulatory decay distances () of 11 short-range TFs (left) and 49 long-range TFs (right). Source data are provided as a Source Data file.