Extension of the Visualization Tool MapMan to Allow Statistical Analysis of Arrays, Display of Cores

Extension of the Visualization Tool MapMan to Allow Statistical Analysis of Arrays, Display of Cores

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Update on MapMan Extension of the Visualization Tool MapMan to Allow Statistical Analysis of Arrays, Display of Coresponding Genes, and Comparison with Known Responses 1 Bjo ¨rn Usadel 2 *, Axel Nagel 2 , Oliver Thimm 3 , Henning Redestig, Oliver E. Blaesing, Natalia Palacios-Rojas 4 , Joachim Selbig, Jan Hannemann, Maria Conceic x a ˜o Piques, Dirk Steinhauser, Wolf-Ru ¨diger Scheible, Yves Gibon, Rosa Morcuende 5 , Daniel Weicht, Svenja Meyer, and Mark Stitt Max Planck Institute of Molecular Plant Physiology, 14476 Golm, Germany (B.U., O.T., H.R., O.E.B., N.P.-R., J.S., J.H., M.C.P., D.S., W.-R.S., Y.G., R.M., D.W., M.S.); and RZPD German Resource Centre for Genome Research, D–14059 Berlin, Germany (A.N., S.M.) MapMan is a user-driven tool that displays large genomics datasets onto diagrams of metabolic pathways or other processes. Here, we present new developments, including improvements of the gene assignments and the user interface, a strategy to visualize multilayered datasets, the incorporation of statistics packages, and extensions of the software to incorporate more biological information including visualization of coresponding genes and horizontal searches for similar global responses across large numbers of arrays. Expression arrays (De Risi et al., 1997; Celis et al., 2000; Michaut et al., 2003; Scheible et al., 2004) and metabolite profiling (Fiehn et al., 2000; Stitt and Fernie, 2003) provide a comprehensive overview of system responses. However, their interpretation de- pends on the availability of appropriate bioinformat- ics tools. While many tools exist to support statistical analysis of profiling data, relatively few tools in- tegrate profiling datasets with preexisting biological knowledge. Examples include GenMAPP (http:// www.GenMAPP.org), PathwayAssist (http://www. ariadnegenomics.com), Pathway Processor (Grosu et al., 2002), BioMiner (http://www.zbi.uni-saarland. de/chair/projects/BioMiner/index.shtml), and the Saccharomyces genome database (Christie et al., 2004). GenMAPP, Pathway Processor, and the Sac- charomyces genome database include many yeast ( Saccharomyces cerevisiae ) pathway diagrams and pro- vide yeast researchers with powerful tools to visual- ize their experiments. This is especially true for Pathway Processor, which also supports statistical analysis. However, these tools are of limited utility for plant research because they are based on micro- bial or animal systems, contain irrelevant categories, lack plant-specific pathways and processes, and lack predefined plant pathways. The plant-specific tool Aracyc (Mueller et al., 2003) is easy to use and intuitive, but suffers from the limitation of being designed as an online tool and from offering only prebuilt pathways. In addition to stand-alone studies, large public do- main databases (e.g. AtGenExpress) that integrate datasets from hundreds of profiling studies are being established. These allow more sophisticated questions to be posed. Tools have been developed to query the responses of individual genes horizontally across hun- dreds of physiological or environmental treatments or developmental series (Rhee et al., 2003; Craigon et al., 2004; Zimmermann et al., 2004). The next level is to
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This note was uploaded on 08/01/2009 for the course HORT hor-11-12 taught by Professor Park during the Spring '09 term at A.T. Still University.

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Extension of the Visualization Tool MapMan to Allow Statistical Analysis of Arrays, Display of Cores

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