ChIP-Atlas: a data-mining suite powered by full integration of public ChIP-seq data

Shinya Oki, Tazro Ohta, Go Shioi, Hideki Hatanaka, Osamu Ogasawara, Yoshihiro Okuda, Hideya Kawaji, Ryo Nakaki, Jun Sese, Chikara Meno

Research output: Contribution to journalArticlepeer-review

400 Citations (Scopus)


We have fully integrated public chromatin chromatin immunoprecipitation sequencing (ChIP-seq) and DNase-seq data (n > 70,000) derived from six representative model organisms (human, mouse, rat, fruit fly, nematode, and budding yeast), and have devised a data-mining platform—designated ChIP-Atlas ( ChIP-Atlas is able to show alignment and peak-call results for all public ChIP-seq and DNase-seq data archived in the NCBI Sequence Read Archive (SRA), which encompasses data derived from GEO, ArrayExpress, DDBJ, ENCODE, Roadmap Epigenomics, and the scientific literature. All peak-call data are integrated to visualize multiple histone modifications and binding sites of transcriptional regulators (TRs) at given genomic loci. The integrated data can be further analyzed to show TR–gene and TR–TR interactions, as well as to examine enrichment of protein binding for given multiple genomic coordinates or gene names. ChIP-Atlas is superior to other platforms in terms of data number and functionality for data mining across thousands of ChIP-seq experiments, and it provides insight into gene regulatory networks and epigenetic mechanisms.

Original languageEnglish
Article numbere46255
JournalEMBO Reports
Issue number12
Publication statusPublished - Dec 2018

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Biology
  • Genetics


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