DASS-GUI: a user interface for identification and analysis of significant patterns in non-sequential data
Many large "omics" data sets have been published and many more are expected in the near future. New analysis methods are needed for best exploitation. We have developed a graphical user interface (GUI) for easy data analysis. Our DASS approach (Discovery of All Significant Substructures) elucidates the underlying modularity, a typical feature of complex biological data. It is related to biclustering and other data mining approaches. Importantly, DASS-GUI also allows handling of multi-sets and calculation of statistical significances. DASS-GUI contains tools for further analysis of the identified patterns: analysis of the pattern hierarchy, enrichment analysis, module validation, analysis of additional numerical data, easy handling of synonymous names, clustering, filtering and merging. Different export options allow easy usage of additional tools such as Cytoscape.
Source code, precompiled binaries for different systems, a comprehensive tutorial, case studies and many additional datasets are freely available at http://www.ifr.ac.uk/dass/gui/. DASS-GUI is implemented in Qt.
* Hollunder, J., * Friedel, M., Kuiper, M., Wilhelm, T. (2010) DASS-GUI: a user interface for identification and analysis of significant patterns in non-sequential data. Bioinformatics 26(7):987-9. *contributed equally
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Bioinformatics & Evolutionary Genomics
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