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MultiChIPmixHMM: an R package for ChIP-chip data analysis modeling spatial dependencies and multiple replicates

Caroline Bérard126*, Michael Seifert89, Tristan Mary-Huard127 and Marie-Laure Martin-Magniette12345

Author Affiliations

1 INRA, UMR 518 MIA, F-75005 Paris, France

2 AgroParisTech, UMR 518 MIA, F-75005 Paris, France

3 INRA, UMR 1165 URGV, Evry, France

4 UEVE, UMR URGV, Evry, France

5 CNRS, ERL 8196 UMR URGV, Evry, France

6 Université de Rouen, LITIS EA 4108, Mont-Saint-Aignan, France

7 UMR de Génétique Végétale, INRA, Université Paris-Sud, CNRS, Gif-sur-Yvette, France

8 Innovative Methods of Computing, Center for Information Services and High Performance Computing, Technical University Dresden, Dresden, Germany

9 Cellular Networks and Systems Biology, Biotechnology Center, Technical University Dresden, Dresden, Germany

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BMC Bioinformatics 2013, 14:271  doi:10.1186/1471-2105-14-271

Published: 9 September 2013

Abstract

Background

Chromatin immunoprecipitation coupled with hybridization to a tiling array (ChIP-chip) is a cost-effective and routinely used method to identify protein-DNA interactions or chromatin/histone modifications. The robust identification of ChIP-enriched regions is frequently complicated by noisy measurements. This identification can be improved by accounting for dependencies between adjacent probes on chromosomes and by modeling of biological replicates.

Results

MultiChIPmixHMM is a user-friendly R package to analyse ChIP-chip data modeling spatial dependencies between directly adjacent probes on a chromosome and enabling a simultaneous analysis of replicates. It is based on a linear regression mixture model, designed to perform a joint modeling of immunoprecipitated and input measurements.

Conclusion

We show the utility of MultiChIPmixHMM by analyzing histone modifications of Arabidopsis thaliana. MultiChIPmixHMM is implemented in R and including functions in C, freely available from the CRAN web site: http://cran.r-project.org webcite.