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Investigates developmental epigenomes and transcriptomes that are related to De novo mutations (DNMs) in developmental disorders. EpiDenovo is a database for exploring the associations between embryonic epigenetic regulation and DNMs in developmental disorders, including neuropsychiatric disorders and congenital heart disease. This resource is based on the epigenomes of publicly available chromatin immunoprecipitation sequencing (ChIP-seq) and chromatin accessibility data during the embryonic development of mammals, including humans and mice.

H(O)TA / Hairpin (Oxidative) bisulfite sequencing Time course Analyzer

Infers (hydroxy-)methylation levels and efficiencies of the involved enzymes at a certain DNA locus. H(O)TA is based on the construction of two coupled Hidden Markov Models (HMMs). It is able to take into account all relevant conversion errors. This tool predicts only the methylation levels and efficiencies, merged with the corresponding unknown hydroxylation values, of a given region. It is capable of analyzing time course data from hairpin bisulfite sequencing and hairpin oxidative bisulfite sequencing in the same time.

HDACiDB / Histone DeACetylase inhibitor DataBase

Enables rapid access to data relevant to the development of epigenetic modulators. HDACiDB aims to help the user to bring precision cancer medicine a step closer. It contains a set of histone deacetylase inhibitor (HDACi) that comprises 1,445 chemical compounds, including 419 natural and 1,026 synthetic ones having the potential to inhibit histone deacetylation. The database offers information about source of origin, molecular properties, drug likeness, as well as bioavailability for each inhibitor.

dbEM / database of Epigenetic Modifiers

A database of about 167 epigenetic modifiers/proteins, which are considered as potential cancer targets. In dbEM, modifiers are classified on functional basis and comprise of 48 histone methyl transferases, 33 chromatin remodelers and 31 histone demethylases. dbEM maintains the genomic information like mutations, copy number variation and gene expression in thousands of tumor samples, cancer cell lines and healthy samples. This information is obtained from public resources viz. COSMIC, CCLE and 1000-genome project. Gene essentiality data retrieved from COLT database further highlights the importance of various epigenetic proteins for cancer survival. We have also reported the sequence profiles, tertiary structures and post-translational modifications of these epigenetic proteins in cancer. It also contains information of 54 drug molecules against different epigenetic proteins.


Displays sequencing data from Roadmap Epigenomics project, powered by a local mirror of UCSC Genome Browser. VizHub is a visualization tool. The Roadmap Epigenomics Mapping Consortium was launched with the goal of producing a public resource of human epigenomic data to catalyze basic biology and disease-oriented research. The Consortium is also committed to the development, standardization and dissemination of protocols, reagents and analytical tools to enable the research community to utilize, integrate and expand upon this body of data.


Uses multiple tools to identify peaks. SigSeeker works about existing peak comparisons by including peak overlaps of varying minimal width and peak-intensity correlation models. This is done to refine peak predictions in an unsupervised approach. It combines positional and quantitative filtering as part of a peak-calling ensemble. This tool can be used with any peak-calling approach whose input (1) consists of aligned sequencing reads in the BED file format or (2) is in a form that can be converted to BED (e.g. SAM, BAM, ELAND) and that generates peak lists in BED or compatible formats.