MOTIVATION: It has been suggested that presumably distinct classes of genomic regulatory elements may actually share common sets of features and mechanisms. However, there has been no genome-wide assessment of the prevalence of this phenomenon. RESULTS: To evaluate this possibility, we performed a bioinformatic screen for the existence of compound regulatory elements in the human genome. We identified numerous such colocated boundary and enhancer elements from human CD4(+) T cells. We report evidence that such compound regulatory elements possess unique chromatin features and facilitate cell type-specific functions related to inflammation and immune response in CD4(+) T cells.

SUMMARY: Although some histone modification chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) signals show abrupt peaks across narrow and specific genomic locations, others have diffuse distributions along chromosomes, and their large contiguous enrichment landscapes are better modeled as broad peaks. Here, we present BroadPeak, an algorithm for the identification of such broad peaks from diffuse ChIP-seq datasets. We show that BroadPeak is a linear time algorithm that requires only two parameters, and we validate its performance on real and simulated histone modification ChIP-seq datasets. BroadPeak calls peaks that are highly coincident with both the underlying ChIP-seq tag count distributions and relevant biological features, such as the gene bodies of actively transcribed genes, and it shows superior overall recall and precision of known broad peaks from simulated datasets. AVAILABILITY: The source code and documentations are available at http://jordan.biology.gatech.edu/page/software/broadpeak/.

MOTIVATION: Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is widely used in biological research. ChIP-seq experiments yield many ambiguous tags that can be mapped with equal probability to multiple genomic sites. Such ambiguous tags are typically eliminated from consideration resulting in a potential loss of important biological information. RESULTS: We have developed a Gibbs sampling-based algorithm for the genomic mapping of ambiguous sequence tags. Our algorithm relies on the local genomic tag context to guide the mapping of ambiguous tags. The Gibbs sampling procedure we use simultaneously maps ambiguous tags and updates the probabilities used to infer correct tag map positions. We show that our algorithm is able to correctly map more ambiguous tags than existing mapping methods. Our approach is also able to uncover mapped genomic sites from highly repetitive sequences that can not be detected based on unique tags alone, including transposable elements, segmental duplications and peri-centromeric regions. This mapping approach should prove to be useful for increasing biological knowledge on the too often neglected repetitive genomic regions. AVAILABILITY: http://esbg.gatech.edu/jordan/software/map CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.