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

Shinya Oki(Kyushu University), Tazro Ohta(Research Organization of Information and Systems), Go Shioi, Hideki Hatanaka(Japan Science and Technology Agency), Osamu Ogasawara(National Institute of Genetics), Yoshihiro Okuda(National Institute of Genetics), Hideya Kawaji(RIKEN), Ryo Nakaki(The University of Tokyo), Jun Sese(National Institute of Advanced Industrial Science and Technology), Chikara Meno(Kyushu University)
EMBO Reports
November 9, 2018
Cited by 818Open Access
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Abstract

> 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 (http://chip-atlas.org). 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.


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