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

Area of Science:

• Genomics
• Epigenetics
• Bioinformatics

Background:

• Chromatin immunoprecipitation sequencing (ChIP-seq) and DNase-seq are crucial for understanding gene regulation.
• Vast amounts of public ChIP-seq and DNase-seq data exist across multiple model organisms.
• Integrating and mining this data presents a significant challenge for researchers.

Purpose of the Study:

• To develop a comprehensive data-mining platform for public ChIP-seq and DNase-seq data.
• To provide a centralized resource for analyzing epigenetic modifications and transcriptional regulator binding.
• To facilitate the study of gene regulatory networks and epigenetic mechanisms.

Main Methods:

• Integrated over 70,000 public ChIP-seq and DNase-seq datasets from six model organisms (human, mouse, rat, fruit fly, nematode, budding yeast).
• Developed ChIP-Atlas, a data-mining platform accessible at http://chip-atlas.org.
• Utilized data from NCBI Sequence Read Archive (SRA), including GEO, ArrayExpress, DDBJ, ENCODE, Roadmap Epigenomics, and literature.

Main Results:

• ChIP-Atlas visualizes alignment and peak-call results for all integrated public ChIP-seq and DNase-seq data.
• The platform integrates peak-call data to visualize histone modifications and transcriptional regulator (TR) binding sites at genomic loci.
• Enables analysis of TR-gene and TR-TR interactions, and enrichment of protein binding for specified genomic coordinates or gene names.

Conclusions:

• ChIP-Atlas offers superior data volume and functionality for mining thousands of ChIP-seq experiments.
• The platform provides valuable insights into gene regulatory networks and epigenetic mechanisms.
• ChIP-Atlas serves as a powerful resource for researchers in genomics and epigenetics.