Abstract
High-density tiling microarrays are increasingly used in combination with chromatin immunoprecipitation (ChIP) assays to delineate the regulation of gene expression. Besides the technical challenges inherent to such complex biological assays, a critical, often daunting issue is the correct interpretation of the sheer amount of raw data generated by utilizing computational methods. Here, we go through the main steps of this intricate process, including optimized chromatin immunoprecipitation on chip (ChIP-chip) data normalization, peak detection, as well as quality control reports. We also describe convenient standalone software suites, including our own, CoCAS, which works on the latest generation of Agilent high-density arrays, allows dye-swap, replicate correlation, and easy connection with genome browsers for results interpretation, or with, e.g., other peak detection algorithms. Overall, the guidelines described herein provide an effective introduction to ChIP-chip technology and analysis.
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Acknowledgments
Work in the Ferrier laboratory is supported by Inserm, CNRS, the Agence Nationale de la Recherche (ANR), Institut National du Cancer (INCa), Association pour la Recherche sur le Cancer (ARC), Fondation Princesse Grace de Monaco, Fondation de France, Association Laurette Fugain, and Commission of the European Communities. PC and TB were supported by fellowships from, respectively, INCa and Marseille-Nice Genopole and ANR 06-BYOS-0006; both are now fellows from the Fondation de la Recherche Médicale (FRM). We also extend our thanks to Jean-Christophe Andrau, Salvatore Spicuglia, Frederic Koch, and Frederic Rosa for their comments, as well as Virginia Cauchy for her corrections.
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Cauchy, P., Benoukraf, T., Ferrier, P. (2011). Processing ChIP-Chip Data: From the Scanner to the Browser. In: Mayer, B. (eds) Bioinformatics for Omics Data. Methods in Molecular Biology, vol 719. Humana Press. https://doi.org/10.1007/978-1-61779-027-0_12
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DOI: https://doi.org/10.1007/978-1-61779-027-0_12
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