Supriya Ghosh (Editor)

Metascape

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Original author(s)
  
Metascape Team

License
  
proprietary

Type
  
Bioinformatics

Website
  
http://metascape.org

Developer(s)
  
Sanford Burnham, UCSD, GNF

Stable release
  
3.0 / 2 November 2016; 4 months ago (2016-11-02)

Metascape is a free gene annotation and analysis resource that helps biologists make sense of one or multiple gene lists. Metascape provides automated meta-analysis tools to understand either common or unique pathways and protein networks within a group of orthogonal target-discovery studies.

Contents

History

At the "OMICs" age it is important to gain biological insights into a list of genes. Although a number of bioinformatics sources exist for this purpose, such as DAVID, they are not all free, easy to use, and well maintained. To analyze multiple lists of genes originated from orthogonal but complementary "OMICs" studies, tools often require computational skills that are beyond the reach of many biologists. A team of scientists self-organized to create and released Metascape on Oct 8, 2015. Metascape has gone through multiple releases since then. The latest release 3.0 supports key model organisms, pathway enrichment analysis, protein-protein interaction network and component analysis, automatic presentation of the results as publication-ready web report, Excel and PowerPoint presentations. The first Metascape application was published on Dec 9, 2015.

Analysis Workflow

Metascape implements a CAME analysis workflow:

  • ID Conversion: Convert gene identifiers from popular types (such as Symbol, RefSeq, Ensembl, UniProt, UCSC) into human Entrez gene IDs and vice versa.
  • Annotation: Extract from dozens of function-relevant gene annotations, including protein families, transmembrane/secreted predictions, disease associations, compound associations, etc.
  • Membership: Flag gene memberships based on a custom keyword search within selected ontologies, e.g., highlight known "invasion" genes.
  • Enrichment: Identify enriched biological themes, particularly GO terms, KEGG, Reactome, BioCarta, as well as other pathways and data sets collected in MSigDB, etc. In addition, enriched ontology terms are automatically clustered to reduce redundancy for easier interpretation. Protein-protein interaction networks are constructed based on BioGRID, OmniPath, InWeb_IM and dense components are identified and biologically interpreted.

    • Analysis Report

    All analysis results are presented in a web report, which contains Excel annotation and enrichment sheets, PowerPoint slides, and custom analysis files (e.g., .cys file by Cytoscape, .svg by Circos) for further offline analysis or processing.

    References

    Metascape Wikipedia
    (Text) CC BY-SA