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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



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.


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.


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: webcite.