A short survey of computational analysis methods in analysing ChIP-seq data

Hyunmin Kim, Jihye Kim, Heather Selby, Dexiang Gao, Tiejun Tong, Tzu Lip Phang, Aik Choon Tan

Research output: Contribution to journalReview articlepeer-review

18 Citations (Scopus)


Chromatin immunoprecipitation followed by massively parallel next-generation sequencing (ChIP-seq) is a valuable experimental strategy for assaying protein-DNA interaction over the whole genome. Many computational tools have been designed to find the peaks of the signals corresponding to protein binding sites. In this paper, three computational methods, ChIP-seq processing pipeline (spp), PeakSeq and CisGenome, used in ChIP-seq data analysis are reviewed. There is also a comparison of how they agree and disagree on finding peaks using the publically available Signal Transducers and Activators of Transcription protein 1 (STAT1) and RNA polymerase II (PolII) datasets with corresponding negative controls.

Original languageEnglish
Pages (from-to)117-123
Number of pages7
JournalHuman Genomics
Issue number2
Publication statusPublished - 2011 Jan

Bibliographical note

Funding Information:
We would like to thank Dr David L. Bentley for his constructive comments on the initial draft of this manuscript. H.K. is supported by NIH grant to GM063873 to D.L. Bentley.


  • Bioinformatics
  • CHIP-Seq analysis
  • Comparative analysis
  • Next-generation sequencing

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Drug Discovery


Dive into the research topics of 'A short survey of computational analysis methods in analysing ChIP-seq data'. Together they form a unique fingerprint.

Cite this