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Open Access Highly Accessed Research article

ChIPseqR: analysis of ChIP-seq experiments

Peter Humburg124*, Chris A Helliwell3, David Bulger1 and Glenn Stone2

Author Affiliations

1 Department of Statistics, Macquarie University, North Ryde, NSW 2109, Australia

2 CSIRO Mathematical and Information Sciences, North Ryde, NSW 2113, Australia

3 CSIRO Plant Industry, GPO Box 1600, Canberra 2601, Australia

4 The Wellcome Trust Centre for Human Genetics, Oxford OX3 7BN, UK

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BMC Bioinformatics 2011, 12:39  doi:10.1186/1471-2105-12-39

Published: 31 January 2011

Abstract

Background

The use of high-throughput sequencing in combination with chromatin immunoprecipitation (ChIP-seq) has enabled the study of genome-wide protein binding at high resolution. While the amount of data generated from such experiments is steadily increasing, the methods available for their analysis remain limited. Although several algorithms for the analysis of ChIP-seq data have been published they focus almost exclusively on transcription factor studies and are usually not well suited for the analysis of other types of experiments.

Results

Here we present ChIPseqR, an algorithm for the analysis of nucleosome positioning and histone modification ChIP-seq experiments. The performance of this novel method is studied on short read sequencing data of Arabidopsis thaliana mononucleosomes as well as on simulated data.

Conclusions

ChIPseqR is shown to improve sensitivity and spatial resolution over existing methods while maintaining high specificity. Further analysis of predicted nucleosomes reveals characteristic patterns in nucleosome sequences and placement.