Starr: Simple Tiling ARRay analysis of Affymetrix ChIP-chip data

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  • Zacher, Benedikt
    • Other Affiliation: Ludwig-Maximilians-University of Munich
  • Kuan, Pei Fen
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Tresch, Achim
    • Other Affiliation: Ludwig-Maximilians-University of Munich
Abstract
  • Background Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is an assay used for investigating DNA-protein-binding or post-translational chromatin/histone modifications. As with all high-throughput technologies, it requires thorough bioinformatic processing of the data for which there is no standard yet. The primary goal is to reliably identify and localize genomic regions that bind a specific protein. Further investigation compares binding profiles of functionally related proteins, or binding profiles of the same proteins in different genetic backgrounds or experimental conditions. Ultimately, the goal is to gain a mechanistic understanding of the effects of DNA binding events on gene expression. Results We present a free, open-source R/Bioconductor package Starr that facilitates comparative analysis of ChIP-chip data across experiments and across different microarray platforms. The package provides functions for data import, quality assessment, data visualization and exploration. Starr includes high-level analysis tools such as the alignment of ChIP signals along annotated features, correlation analysis of ChIP signals with complementary genomic data, peak-finding and comparative display of multiple clusters of binding profiles. It uses standard Bioconductor classes for maximum compatibility with other software. Moreover, Starr automatically updates microarray probe annotation files by a highly efficient remapping of microarray probe sequences to an arbitrary genome. Conclusion Starr is an R package that covers the complete ChIP-chip workflow from data processing to binding pattern detection. It focuses on the high-level data analysis, e.g., it provides methods for the integration and combined statistical analysis of binding profiles and complementary functional genomics data. Starr enables systematic assessment of binding behaviour for groups of genes that are alingned along arbitrary genomic features.
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  • Article
Rights statement
  • In Copyright
Rights holder
  • Benedikt Zacher et al.; licensee BioMed Central Ltd.
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Journal title
  • BMC Bioinformatics
Journal volume
  • 11
Journal issue
  • 1
Page start
  • 194
Language
  • English
Is the article or chapter peer-reviewed?
  • Yes
ISSN
  • 1471-2105
Bibliographic citation
  • BMC Bioinformatics. 2010 Apr 17;11(1):194
Publisher
  • BioMed Central Ltd
Access right
  • Open Access
Date uploaded
  • August 23, 2012

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