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Gene set enrichment analysis (GSEA) is a widely used technique in transcriptomic data analysis that uses a database of predefined gene sets to rank lists of genes from microarray studies to identify significant and coordinated changes in gene expression data. While GSEA has been playing a significant role in understanding transcriptomic data, no similar tools are currently available for understanding metabolomic data. Here, we introduce a web-based server, called Metabolite Set Enrichment Analysis (MSEA), to help researchers identify and interpret patterns of human or mammalian metabolite concentration changes in a biologically meaningful context. Key to the development of MSEA has been the creation of a library of approximately 1000 predefined metabolite sets covering various metabolic pathways, disease states, biofluids, and tissue locations. MSEA also supports user-defined or custom metabolite sets for more specialized analysis. MSEA offers three different enrichment analyses for metabolomic studies including overrepresentation analysis (ORA), single sample profiling (SSP) and quantitative enrichment analysis (QEA). ORA requires only a list of compound names, while SSP and QEA require both compound names and compound concentrations. MSEA generates easily understood graphs or tables embedded with hyperlinks to relevant pathway images and disease descriptors. For non-mammalian or more specialized metabolomic studies, MSEA allows users to provide their own metabolite sets for enrichment analysis. The MSEA server also supports conversion between metabolite common names, synonyms, and major database identifiers. MSEA has the potential to help users identify obvious as well as 'subtle but coordinated' changes among a group of related metabolites that may go undetected with conventional approaches. MSEA is freely available at http://www.msea.ca.
Pubmed ID: 20457745 RIS Download
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An interactive, visual database containing more than 350 small molecule pathways found in humans. More than 2/3 of these pathways (>280) are not found in any other pathway database. SMPDB is designed specifically to support pathway elucidation and pathway discovery in metabolomics, transcriptomics, proteomics and systems biology. It is able to do so, in part, by providing exquisitely detailed, fully searchable, hyperlinked diagrams of human metabolic pathways, metabolic disease pathways, metabolite signaling pathways and drug-action pathways. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Each small molecule is hyperlinked to detailed descriptions contained in the HMDB or DrugBank and each protein or enzyme complex is hyperlinked to UniProt. All SMPDB pathways are accompanied with detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram. The database is easily browsed and supports full text, sequence and chemical structure searching. Users may query SMPDB with lists of metabolite names, drug names, genes / protein names, SwissProt IDs, GenBank IDs, Affymetrix IDs or Agilent microarray IDs. These queries will produce lists of matching pathways and highlight the matching molecules on each of the pathway diagrams. Gene, metabolite and protein concentration data can also be visualized through SMPDB''s mapping interface. All of SMPDB''s images, image maps, descriptions and tables are downloadable.
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