Motivation: The growing amount of regulatory data from the ENCODE, Roadmap Epigenomics and other consortia provides a wealth of opportunities to investigate the functional impact of single nucleotide polymorphisms (SNPs). Yet, given the large number of regulatory datasets, researchers are posed with a challenge of how to efficiently utilize them to interpret the functional impact of SNP sets. Results: We developed the GenomeRunner web server to automate systematic statistical analysis of SNP sets within a regulatory context. Besides defining the functional impact of SNP sets, GenomeRunner implements novel regulatory similarity/differential analyses, and cell type-specific regulatory enrichment analysis. Validated against literature-and disease ontology-based approaches, analysis of 39 disease/trait-associated SNP sets demonstrated that the functional impact of SNP sets corresponds to known disease relationships. We identified a group of autoimmune diseases with SNPs distinctly enriched in the enhancers of T helper cell subpopulations, and demonstrated relevant cell type-specificity of the functional impact of other SNP sets. In summary, we show how systematic analysis of genomic data within a regulatory context can help interpreting the functional impact of SNP sets. Availability and Implementation: GenomeRunner web server is freely available at http://www.inte grativegenomics.org/. Contact:

Supplementary data are available at Bioinformatics online.

ATM and ATR are cellular kinases with a well-characterized role in the DNA-damage response. Although the complete set of ATM/ATR targets is unknown, they often contain clusters of S/TQ motifs that constitute an SCD domain. In this study, we identified putative ATM/ATR targets that have a conserved SCD domain across vertebrates. Using this approach, we have identified novel putative ATM/ATR targets in pathways known to be under direct control of these kinases. Our analysis has also unveiled significant enrichment of SCD-containing proteins in cellular pathways, such as vesicle trafficking and actin cytoskeleton, where a regulating role for ATM/ATR is either unknown or poorly understood, hinting at a much broader and overarching role for these kinases in the cell. Of particular note is the overrepresentation of conserved SCD-containing proteins involved in pathways related to neural development. This finding suggests that ATM/ATR could be directly involved in controlling this process, which may be linked to the adverse neurological effects observed in patients with mutations in ATM.

Objective Visually-obvious abnormalities in the resting baseline EEG – slowing, spiking and high-frequency oscillations (HFOs) - are cardinal, though incompletely understood, features of the seizure onset zone in focal epilepsy. We hypothesized that evidence of cortical network dysfunction in temporal lobe epilepsy (TLE) would persist in the absence of visually-classifiable abnormalities in the baseline EEG recorded within the conventional passband, and that metrics of such dysfunction could serve as a lateralizing diagnostic in TLE. Methods Epochs of resting EEG without significant abnormalities in light sleep over several days were compared between a group of 10 patients with proven TLE and 10 subjects without epilepsy. A novel laterality metric computed from the line length of normalized power spectra from the temporal channels was compared between the two groups. Results Significant group differences in spectral line length laterality metric were found between the TLE and control group. At the individual level, seven of 10 TLE patients had highly significant laterality metrics, all concordant with the known laterality of their disease. Significance Detailed spectral analysis offers novel insight into TLE network behavior, independent of the orthodox abnormalities of EEG slowing, spikes or HFOs. The results may be deployed in a practical diagnostic manner, offer insight into the EEG manifestations of disordered cellular network architecture in TLE, and maybe understood through simple analogy with the theory of linear time-invariant physical systems.

The application was developed using Pearl and Python, and is available at the following URL: http://ustbioinfo.webfactional.com/scd/.