Predicts histone modification and DNA methylation patterns from DNA motifs. Epigram is an analysis pipeline used to systematically identify DNA motifs that are predictive of epigenomic modifications. It reveals the cis-regulatory program that is read by the dynamic genetic network to shape the epigenome. In particular, Epigram’s motifs are significantly correlated with almost double the number of H3K27ac regions when compared to five times the number of known Transcription Factor (TF) motifs.

A tool for identification of enriched regions at multiple length scales that the user can select, using the data from ChIP-Seq experiments. MUSIC performs favorably in terms of accuracy and reproducibility compared with other methods. In particular, analysis of RNA Polymerase II data reveals a clear distinction between the stalled and elongating forms of the polymerase.

An HMM-based approach to detect and analyze differential peaks in two sets of ChIP-seq data from distinct biological conditions with replicates. THOR performs genomic signal processing, normalization of multiple signals, peak calling and p-value calculation in an integrated framework.

A web resource that includes a large collection of genome-wide ChIP-Seq experiments performed on TFs, histone modifications, RNA polymerases and others.

Identifies cell-type-specific regulatory elements (CSREs) in the human genome. dCMA is a computational framework capable of identifying genomic regions, containing distinctive chromatin modifications that are unique to each cell type. This framework demonstrates the power of a differential comparative epigenomics strategy in deciphering aspects of the human genome and characterizing cell specificity.

Handles all the bins together, capturing both neighboring range and long range interactions among input features, as well as automatically extract important features. DeepChrome is a unified Convolutional Neural Networks (CNNs) framework that automatically learns combinatorial interactions among histone modification marks to predict the gene expression. Through this model, DeepChrome incorporates representations of both local neighboring bins as well as the whole gene.

A tool to build a transcriptional regulatory network composing of histone modification and transcription factor binding in promoters and interactions between factors in these two fields. Given a set of categorized genes, EpiRegNet would find the factors which contribute most to the difference in the gene expression level based on the statistic tests on the enrichment of each factor in gene promoters. Furthermore, the tool perform correlation tests to study the relation between these factors, and draw the regulatory network to declare their cooperative or competitive roles in activation or repression of gene expression.

Allows the analysis and annotation of coverage islands within individual read alignment (BAM) files of histone modification ChIPseq datasets harboring broad chromatin domains. SUPERmerge allows flexible regulation of a variety of read pileup parameters, thereby revealing how read islands aggregate into areas of coverage across the genome and what annotation features they map to within individual biological replicates. It can be useful for investigating low sample size ChIP-seq experiments.

Integrative analyses of epigenetic data promise a deeper understanding of the epigenome. Epidaurus is a bioinformatics tool used to effectively reveal inter-dataset relevance and differences through data aggregation, integration and visualization.