MOTIVATION: Tools aiding in collaborative data analysis are becoming ever more important as researchers work together over long distances. We present an extension to the Gaggle framework, which has been widely adopted as a tool to enable data exchange between different analysis programs on one computer. RESULTS: Our program, GaggleBridge, transparently extends this functionality to allow data exchange between Gaggle users at different geographic locations using network communication. GaggleBridge can automatically set up SSH tunnels to traverse firewalls while adding some security features to the Gaggle communication. AVAILABILITY: GaggleBridge is available as open-source software implemented in the Java language at http://it.inf.uni-tuebingen.de/gb. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: High-throughput transcriptomics, proteomics and metabolomics methods have revolutionized our knowledge of biological systems. To gain knowledge from comparative omics studies, strong data integration and visualization features are required. Knowledge gained from these studies is often available in the form of graphs, and their visualization is especially useful in a wide range of systems biology topics, including pathway analysis, interaction networks or gene models. Especially, it is necessary to compare biological models with measured data. This allows the identification of new models and new insights into existing ones. RESULTS: We present MGV, a versatile generic graph viewer for multiomics data. MGV is integrated into Mayday (Battke et al., 2010). It extends Mayday's visual analytics capabilities by integrating a wide range of biological models, high-throughput data and meta information to display enriched graphs that combine data and models. A wide range of tools is available for visualization of nodes, data-aware graph layout as well as automatic and manual aggregation and refinement of the data. We show the usefulness of MGV applied to several problems, including differential expression of alternative transcripts, transcription factor interaction, cross-study clustering comparison and integration of transcriptomics and metabolomics data for pathway analysis. AVAILABILITY: MGV is a open-source software implemented in Java and freely available as a part of Mayday at www.microarray-analysis.org/mayday. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined, easy to apply methods with programmer's access to the data are important requirements for any analysis framework. Mayday is an open source platform with emphasis on visual data exploration and analysis. Many built-in methods for clustering, machine learning and classification are provided for dissecting complex datasets. Plugins can easily be written to extend Mayday's functionality in a large number of ways. As Java program, Mayday is platform-independent and can be used as Java WebStart application without any installation. Mayday can import data from several file formats, database connectivity is included for efficient data organization. Numerous interactive visualization tools, including box plots, profile plots, principal component plots and a heatmap are available, can be enhanced with metadata and exported as publication quality vector files. RESULTS: We have rewritten large parts of Mayday's core to make it more efficient and ready for future developments. Among the large number of new plugins are an automated processing framework, dynamic filtering, new and efficient clustering methods, a machine learning module and database connectivity. Extensive manual data analysis can be done using an inbuilt R terminal and an integrated SQL querying interface. Our visualization framework has become more powerful, new plot types have been added and existing plots improved. CONCLUSIONS: We present a major extension of Mayday, a very versatile open-source framework for efficient micro array data analysis designed for biologists and bioinformaticians. Most everyday tasks are already covered. The large number of available plugins as well as the extension possibilities using compiled plugins and ad-hoc scripting allow for the rapid adaption of Mayday also to very specialized data exploration. Mayday is available at http://microarray-analysis.org.