Stephan Symons1, Kay Nieselt. 1. Center for Bioinformatics Tübingen, Faculty of Science, University of Tübingen, 72076 Tübingen, Germany. symons@informatik.uni-tuebingen.de
Abstract
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: symons@informatik.uni-tuebingen.de 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: symons@informatik.uni-tuebingen.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Jianguo Xia; Christopher D Fjell; Matthew L Mayer; Olga M Pena; David S Wishart; Robert E W Hancock Journal: Nucleic Acids Res Date: 2013-06-12 Impact factor: 16.971