Background: Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is a high-throughput assay for DNA-protein-binding or post-translational chromatin/histone modifications. However, the raw microarray intensity readings themselves are not immediately useful to researchers, but require a number of bioinformatic analysis steps. Identified enriched regions need to be bioinformatically annotated and compared to related datasets by statistical methods.
Results: We present a free, open-source R package Ringo that facilitates the analysis of ChIP-chip experiments by providing functionality for data import, quality assessment, normalization and visualization of the data, and the detection of ChIP-enriched genomic regions.
Conclusion: Ringo integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It facilitates the construction of programmed analysis workflows, offers benefits in scalability, reproducibility and methodical scope of the analyses and opens up a broad selection of follow-up statistical and bioinformatic methods.