An integrated ChIP-seq analysis platform with customizable workflows

BMC Bioinformatics. 2011 Jul 7;12:277. doi: 10.1186/1471-2105-12-277.


Background: Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the identification of peaks (i.e., genomic locations with high density of mapped sequence reads). The next step consists of interpreting the biological meaning of the peaks through their association with known genes, pathways, regulatory elements, and integration with other experiments. Although several programs have been published for the analysis of ChIP-seq data, they often focus on the peak detection step and are usually not well suited for thorough, integrative analysis of the detected peaks.

Results: To address the peak interpretation challenge, we have developed ChIPseeqer, an integrative, comprehensive, fast and user-friendly computational framework for in-depth analysis of ChIP-seq datasets. The novelty of our approach is the capability to combine several computational tools in order to create easily customized workflows that can be adapted to the user's needs and objectives. In this paper, we describe the main components of the ChIPseeqer framework, and also demonstrate the utility and diversity of the analyses offered, by analyzing a published ChIP-seq dataset.

Conclusions: ChIPseeqer facilitates ChIP-seq data analysis by offering a flexible and powerful set of computational tools that can be used in combination with one another. The framework is freely available as a user-friendly GUI application, but all programs are also executable from the command line, thus providing flexibility and automatability for advanced users.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Chromatin Immunoprecipitation / methods*
  • Chromosome Mapping*
  • Enhancer Elements, Genetic
  • High-Throughput Nucleotide Sequencing / methods*
  • Histone Code
  • Humans
  • Jurkat Cells
  • Proto-Oncogene Protein c-ets-1 / metabolism
  • Software*
  • Workflow


  • ETS1 protein, human
  • Proto-Oncogene Protein c-ets-1

Associated data

  • GEO/GSE17954