HiChIP: A high-throughput pipeline for integrative analysis of ChIP-Seq data

Huihuang Yan, Jared Evans, Mike Kalmbach, Raymond Moore, Sumit Middha, Stanislav Luban, Liguo Wang, Aditya Bhagwate, Ying Li, Zhifu Sun, Xianfeng Chen, Jean Pierre A. Kocher

Research output: Contribution to journalArticle

21 Scopus citations

Abstract

Background: Chromatin immunoprecipitation (ChIP) followed by next-generation sequencing (ChIP-Seq) has been widely used to identify genomic loci of transcription factor (TF) binding and histone modifications. ChIP-Seq data analysis involves multiple steps from read mapping and peak calling to data integration and interpretation. It remains challenging and time-consuming to process large amounts of ChIP-Seq data derived from different antibodies or experimental designs using the same approach. To address this challenge, there is a need for a comprehensive analysis pipeline with flexible settings to accelerate the utilization of this powerful technology in epigenetics research.Results: We have developed a highly integrative pipeline, termed HiChIP for systematic analysis of ChIP-Seq data. HiChIP incorporates several open source software packages selected based on internal assessments and published comparisons. It also includes a set of tools developed in-house. This workflow enables the analysis of both paired-end and single-end ChIP-Seq reads, with or without replicates for the characterization and annotation of both punctate and diffuse binding sites. The main functionality of HiChIP includes: (a) read quality checking; (b) read mapping and filtering; (c) peak calling and peak consistency analysis; and (d) result visualization. In addition, this pipeline contains modules for generating binding profiles over selected genomic features, de novo motif finding from transcription factor (TF) binding sites and functional annotation of peak associated genes.Conclusions: HiChIP is a comprehensive analysis pipeline that can be configured to analyze ChIP-Seq data derived from varying antibodies and experiment designs. Using public ChIP-Seq data we demonstrate that HiChIP is a fast and reliable pipeline for processing large amounts of ChIP-Seq data.

Original languageEnglish (US)
Article number280
JournalBMC bioinformatics
Volume15
Issue number1
DOIs
StatePublished - Aug 15 2014

Keywords

  • ChIP-Seq
  • Duplicate filtering
  • Irreproducible discovery rate
  • Next-generation sequencing
  • Peak calling

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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