Fig. 4: BIT can identify transcriptional regulators from cancer-type-specific accessible regions.
From: BIT: Bayesian Identification of Transcriptional regulators from epigenomics-based query region sets
a Thirty-two TRs identified by BIT from TCGA cancer-type-specific accessible regions validated by existing literature. b BIT scores of top 10 TRs. Posterior estimates of BIT scores are reported with error bars indicating upper and lower bounds of 95% credible intervals. The center is estimated BIT score. c Jaccard index compares cancer-specific accessible regions between any two cancer types (lower triangle) and the sets of top TRs identified by BIT between any two cancer types (upper triangle). d Cumulative number of BIT-identified top 10 and top 50 TRs with minimum Chronos scores of ≤−2 to >0. e Box plots for the Pearson correlation coefficients between Chronos scores and BIT scores for the top 50 TRs identified by BIT across 209 cell lines from nine cancer types. Here, box plots show the median (center line), 25th and 75th percentiles (box edges), and whiskers extending to the largest or smallest value that is within 1.5 times of the interquartile range, and points beyond this range are plotted as outliers. f Numbers of functionally essential TRs identified in the top 10 and 50 TRs by BIT and state-of-the-art methods (BART, ChIP-Atlas, HOMER, i-cisTarget, WhichTF). g The results of gene ontology enrichment analysis of top 20 TRs identified by BIT from breast cancer. The enrichment analysis uses one-sided Fisher’s exact tests. GO terms are ranked by Benjamini–Hochberg adjusted p values. Source data are provided as a Source Data file. This figure has elements created in BioRender. Lu, Z. (2025) https://BioRender.com/4cshxif.
