Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure.

ChIP-chip is a microarray based technology for determining the genomic locations of chromatin bound factors of interest, such as proteins. Standard ChIP-chip analyses employ peak detection methodologies to generate lists of genomic binding sites. No previously published method exists to enable comparative analyses of enrichment levels derived from datasets examining different experimental conditions. This restricts the use of the technology to binary comparisons of presence or absence of features between datasets. Here we present the R package Sandcastle ­ Software for the Analysis and Normalisation of Data from ChIP-chip AssayS of Two or more Linked Experiments ­ which allows for comparative analyses of data from multiple experiments by normalising all datasets to a common background. Relative changes in binding levels between experimental datasets can thus be determined, enabling the extraction of latent information from ChIP-chip experiments. Novel enrichment detection and peak calling algorithms are also presented, with a range of graphical tools, which facilitate these analyses. The software and documentation are available for download from http://reedlab.cardiff.ac.uk/sandcastle.

3D-DIP-Chip: a microarray-based method to measure genomic DNA damage.

Genotoxins cause DNA damage, which can result in genomic instability. The genetic changes induced have far-reaching consequences, often leading to diseases such as cancer. A wide range of genotoxins exists, including radiations and chemicals found naturally in the environment, and in man-made forms created by human activity across a variety of industries. Genomic technologies offer the possibility of unravelling the mechanisms of genotoxicity, including the repair of genetic damage, enhancing our ability to develop, test and safely use existing and novel materials. We have developed 3D-DIP-Chip, a microarray-based method to measure the prevalence of genomic genotoxin-induced DNA damage. We demonstrate the measurement of both physical and chemical induced DNA damage spectra, integrating the analysis of these with the associated changes in histone acetylation induced in the epigenome. We discuss the application of the method in the context of basic and translational sciences.