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An integrated software system for analyzing ChIP-chip and ChIP-seq data

Nature Biotechnology volume 26, pages 1293–1300 (2008)Cite this article

Abstract

We present CisGenome, a software system for analyzing genome-wide chromatin immunoprecipitation (ChIP) data. CisGenome is designed to meet all basic needs of ChIP data analyses, including visualization, data normalization, peak detection, false discovery rate computation, gene-peak association, and sequence and motif analysis. In addition to implementing previously published ChIP–microarray (ChIP-chip) analysis methods, the software contains statistical methods designed specifically for ChlP sequencing (ChIP-seq) data obtained by coupling ChIP with massively parallel sequencing. The modular design of CisGenome enables it to support interactive analyses through a graphic user interface as well as customized batch-mode computation for advanced data mining. A built-in browser allows visualization of array images, signals, gene structure, conservation, and DNA sequence and motif information. We demonstrate the use of these tools by a comparative analysis of ChIP-chip and ChIP-seq data for the transcription factor NRSF/REST, a study of ChIP-seq analysis with or without a negative control sample, and an analysis of a new motif in Nanog- and Sox2-binding regions.

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Figure 1: The basic framework of CisGenome.
Figure 2: ChIP-seq data processing.
Figure 3: Comparisons between NRSF ChIP-seq and ChIP-chip data.
Figure 4: Analysis of a novel motif in Sox2 and Nanog binding regions.

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Acknowledgements

We thank W. Li for assistance with analyzing the ChIP-chip spike-in data. This research was supported by National Institutes of Health grant HG003903 (to W.H.W.) and the National Human Genome Research Institute's ENCODE project (to R.M.M.). H. Ji is partially supported by the Johns Hopkins Bloomberg School of Public Health Richard L. Gelb Cancer Research Fund.

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Author notes

  1. David S Johnson

    Present address: Present address: Gene Security Network, Inc., 1442 Cortland Avenue, San Francisco, California 94110, USA.,

Authors and Affiliations

  1. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, 21205, Maryland, USA

    Hongkai Ji

  2. Institute for Computational and Mathematical Engineering, Stanford University, Durand Building, 496 Lomita Mall, Stanford, 94305, California, USA

    Hui Jiang

  3. Department of Computer Science, Stanford University, 353 Serra Mall, Stanford, 94305, California, USA

    Wenxiu Ma

  4. Department of Genetics, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, 94305, California, USA

    David S Johnson

  5. HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, 35806, Alabama, USA

    Richard M Myers

  6. Department of Statistics, Stanford University, Sequoia Hall, 390 Serra Mall, Stanford, 94305, California, USA

    Wing H Wong

  7. Department of Health Research and Policy, Stanford University, Sequoia Hall, 390 Serra Mall, Stanford, 94305, California, USA

    Wing H Wong

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  1. Hongkai Ji
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Contributions

H. Ji conceived the study, developed the CisGenome GUI and data analysis algorithms, carried out data analyses and drafted the manuscript. H. Jiang developed the CisGenome browser. W.M. participated in algorithm development and carried out data analyses. D.S.J. and R.M.M. generated NRSF ChIP-chip data. W.H.W. conceived the study and drafted the manuscript. All authors read and revised the manuscript.

Corresponding author

Correspondence to Wing H Wong.

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Ji, H., Jiang, H., Ma, W. et al. An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nat Biotechnol 26, 1293–1300 (2008). https://doi.org/10.1038/nbt.1505

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