Metaanalysis of ChIP-chip Data
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Genome-wide analysis of histone modifications via ChIP-chip (chromatin immunoprecipitation followed by whole genome tiling array hybridization) may generate lists of up to several thousand potential target genes. In the case of the model organism Arabidopsis thaliana, several databases are available to alleviate further characterization and classification of genomic data sets. The term metaanalysis has been coined for this type of multidatabase comparison. In this chapter, we describe open source software and web tools that perform transcriptional and functional analysis of target genes. Sources of transcription data and clustering tools to subdivide genes according to their expression pattern are described. The user is guided through all necessary steps, including data download and formatting. In addition, the Gene Ontology (GO) vocabulary and methods to uncover over- or underrepresented functions among target genes are introduced. Genomic targets of the histone H3K27me3 modification are presented as a case study to demonstrate that metaanalysis can uncover novel functions that were hidden in genomic data sets.
Key wordsMetaanalysis AtGenExpress Hierarchical clustering K-means clustering Gene ontology Functional enrichment analysis
We thank Drs. Seth Davis and Anika Jöcker for critical reading of the manuscript.
- 11.Provart NJ, Zhu T (2003) A browser-based functional classification superviewer for Arabidopsis genomics. Curr Comput Mol Biol 2003:271–272Google Scholar
- 13.Benjamini Y, Yekutieli D (2001) The control of the false discovery rate in multiple testing under dependency. Ann Stat 29:1168–1188Google Scholar