BACKGROUND: The massive amounts of data from next generation sequencing (NGS) methods pose various challenges with respect to data security, storage and metadata management. While there is a broad range of data analysis pipelines, these challenges remain largely unaddressed to date. RESULTS: We describe the integration of the open-source metadata management system iRODS (Integrated Rule-Oriented Data System) with a cancer genome analysis pipeline in a high performance computing environment. The system allows for customized metadata attributes as well as fine-grained protection rules and is augmented by a user-friendly front-end for metadata input. This results in a robust, efficient end-to-end workflow under consideration of data security, central storage and unified metadata information. CONCLUSIONS: Integrating iRODS with an NGS data analysis pipeline is a suitable method for addressing the challenges of data security, storage and metadata management in NGS environments.

Abstract Motivation: Cancer genomes are characterized by the accumulation of point mutations and structural alterations such as copy-number alterations and genomic rearrangements. Among structural changes, systematic analyses of copy-number alterations have provided deeper insight into the architecture of cancer genomes and had led to new potential treatment opportunities. During the course of cancer genome evolution, selection mechanisms are leading to a non-random pattern of mutational events contributing to fitness benefits of the cancer cells. We therefore developed a new method to dissect random from non-random patterns in copy-number data and thereby to assess significantly enriched somatic copy-number aberrations across a set of tumor specimens or cell lines. In contrast to existing approaches, the method is invariant to any strictly monotonous transformation of the input data which results to an insensitivity of differences in tumor purity, array saturation effects and copy-number baseline levels. Results: We applied our approach to recently published datasets of small-cell lung cancer and squamous cell lung cancer and validated its performance by comparing the results to an orthogonal approach. In addition, we found a new deletion peak containing the HLA-A gene in squamous cell lung cancer. Availability: The CGARS program package is available for download at http://www.translational-genomics.uni-koeln.de/scientific-resources/ Documentation and examples are available together with the package. Contact: [email protected] Supplementary Information: Supplementary information is available at Bioinformatics online.

MOTIVATION: In this article we build a model of the CpG dinucleotide substitution rate and use it to challenge the claim that, that rate underwent a sudden mammalian-specific increase approximately 90 million years ago. The evidence supporting this hypothesis comes from the application of a model of neutral substitution rates able to account for elevated CpG dinucleotide substitution rates. With the initial goal of improving that model's accuracy, we introduced a modification enabling us to account for boundary effects arising by the truncation of the Markov field, as well as improving the optimization procedure required for estimating the substitution rates. RESULTS: When using this modified method to reproduce the supporting analysis, the evidence of the rate shift vanished. Our analysis suggests that the CpG-specific rate has been constant over the relevant time period and that the asserted acceleration of the CpG rate is likely an artifact of the original model.