Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data
Top Cited Papers
Open Access
- 30 November 2011
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 28 (3), 373-380
- https://doi.org/10.1093/bioinformatics/btr661
Abstract
Motivation: Metabolomics is a rapidly evolving field that holds promise to provide insights into genotype–phenotype relationships in cancers, diabetes and other complex diseases. One of the major informatics challenges is providing tools that link metabolite data with other types of high-throughput molecular data (e.g. transcriptomics, proteomics), and incorporate prior knowledge of pathways and molecular interactions. Results: We describe a new, substantially redesigned version of our tool Metscape that allows users to enter experimental data for metabolites, genes and pathways and display them in the context of relevant metabolic networks. Metscape 2 uses an internal relational database that integrates data from KEGG and EHMN databases. The new version of the tool allows users to identify enriched pathways from expression profiling data, build and analyze the networks of genes and metabolites, and visualize changes in the gene/metabolite data. We demonstrate the applications of Metscape to annotate molecular pathways for human and mouse metabolites implicated in the pathogenesis of sepsis-induced acute lung injury, for the analysis of gene expression and metabolite data from pancreatic ductal adenocarcinoma, and for identification of the candidate metabolites involved in cancer and inflammation. Availability: Metscape is part of the National Institutes of Health-supported National Center for Integrative Biomedical Informatics (NCIBI) suite of tools, freely available at http://metscape.ncibi.org. It can be downloaded from http://cytoscape.org or installed via Cytoscape plugin manager. Contact:metscape-help@umich.edu; akarnovs@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online.Keywords
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