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GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways

Nature Genetics volume 31, pages 19–20 (2002)Cite this article

DNA microarrays are used to measure simultaneously the expression levels of thousands of genes. New tools are needed to relate the large amounts of microarray data generated to known models of cell biology and biochemistry. We have developed a free stand-alone computer program called GenMAPP (Gene Microarray Pathway Profiler), designed for viewing and analyzing gene expression data in the context of biological pathways. GenMAPP displays gene expression data on pathways by color-coding the genes based on data and criteria provided by the investigator. GenMAPP also has graphics tools for constructing and modifying pathways. In addition, it provides access to annotation for genes and a connection with pathway experts. This program thus provides a new format to organize, publish and share DNA microarray data that will increase our understanding of biology in the genomics era.

Current tools for analyzing microarray data include statistical filters and pattern-finding algorithms such as hierarchical clustering1,2. The power of such tools is that they evaluate the gene expression data without the bias of prior knowledge of gene function, providing a valuable first step in analysis by generating lists of interesting genes. The next logical step is to analyze the gene expression changes in the context of known biological pathways3. Several public and commercial pathway resources currently exist, including the Alliance for Cellular Signaling, BioCarta, EcoCyc4 and MetaCyc5, the Kyoto Encyclopedia of Genes and Genomes6 (KEGG) and PathDB. These databases contain large amounts of curated information, and some (EcoCyc, MetaCyc and KEGG) can also be used to view simple gene expression data sets in the context of pre-existing pathways7,8,9. GenMAPP extends the capabilities of these pathway resources by allowing users to modify pathways for their own use, to design new pathways and to apply complex criteria for viewing gene expression data on those pathways. GenMAPP also complements the current pathway databases by providing a means of freely exchanging pathway-related data among investigators.

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Figure 1: Fatty-acid degradation pathway adapted from a view in GenMAPP.

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Acknowledgements

We thank S. Doniger, N. Fidelman, G. Howard, R. Mahley, S. Ordway, C. Redfern, M. Schambelan, B. Taylor, J. Warrington, K. Weisgraber, S. Young and M. Zeiger for valuable discussions and their contributions to the preparation of this manuscript. Support for this work included funding from the J. David Gladstone Institutes, the San Francisco General Hospital General Clinical Research Center, the National Heart, Lung, and Blood Institute and the NHLBI Programs for Genomic Applications (BayGenomics).

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Authors and Affiliations

  1. Gladstone Institute of Cardiovascular Disease, University of California, San Francisco, 94141-9100, California, USA

    Kam D. Dahlquist, Nathan Salomonis, Karen Vranizan, Steven C. Lawlor & Bruce R. Conklin

  2. Cardiovascular Research Institute, University of California, San Francisco, 94141-9100, California, USA

    Kam D. Dahlquist & Bruce R. Conklin

  3. Departments of Medicine and Molecular and Cellular Pharmacology, University of California, San Francisco, 94141-9100, California, USA

    Bruce R. Conklin

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  1. Kam D. Dahlquist
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  2. Nathan Salomonis
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Correspondence to Bruce R. Conklin.

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Dahlquist, K., Salomonis, N., Vranizan, K. et al. GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nat Genet 31, 19–20 (2002). https://doi.org/10.1038/ng0502-19

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