Strategies for analyzing highly enriched IP-chip datasets
| Autor: | Simon Tavaré, Oscar M. Aparicio, Christopher J. Viggiani, Simon R.V. Knott |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2009 |
| Předmět: |
Normalization (statistics)
Chromatin Immunoprecipitation Population Information Storage and Retrieval Computational biology Biology Bioinformatics lcsh:Computer applications to medicine. Medical informatics Biochemistry 03 medical and health sciences 0302 clinical medicine Structural Biology education Molecular Biology lcsh:QH301-705.5 030304 developmental biology 0303 health sciences education.field_of_study Tiling array Applied Mathematics Methodology Article Gene Expression Profiling Computational Biology Chip Computer Science Applications Dynamic programming lcsh:Biology (General) A priori and a posteriori lcsh:R858-859.7 DNA microarray Chromatin immunoprecipitation 030217 neurology & neurosurgery |
| Zdroj: | BMC Bioinformatics, Vol 10, Iss 1, p 305 (2009) BMC Bioinformatics |
| ISSN: | 1471-2105 |
| Popis: | Background Chromatin immunoprecipitation on tiling arrays (ChIP-chip) has been employed to examine features such as protein binding and histone modifications on a genome-wide scale in a variety of cell types. Array data from the latter studies typically have a high proportion of enriched probes whose signals vary considerably (due to heterogeneity in the cell population), and this makes their normalization and downstream analysis difficult. Results Here we present strategies for analyzing such experiments, focusing our discussion on the analysis of Bromodeoxyruridine (BrdU) immunoprecipitation on tiling array (BrdU-IP-chip) datasets. BrdU-IP-chip experiments map large, recently replicated genomic regions and have similar characteristics to histone modification/location data. To prepare such data for downstream analysis we employ a dynamic programming algorithm that identifies a set of putative unenriched probes, which we use for both within-array and between-array normalization. We also introduce a second dynamic programming algorithm that incorporates a priori knowledge to identify and quantify positive signals in these datasets. Conclusion Highly enriched IP-chip datasets are often difficult to analyze with traditional array normalization and analysis strategies. Here we present and test a set of analytical tools for their normalization and quantification that allows for accurate identification and analysis of enriched regions. |
| Databáze: | OpenAIRE |
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