MetScape 3 for Cytoscape

The MetScape 3 App for Cytoscape provides a bioinformatics framework for the visualization and interpretation of metabolomic and expression profiling data in the context of human metabolism. It allows users to build and analyze networks of genes and compounds, identify enriched pathways from expression profiling data, and visualize changes in metabolite data. Gene expression and/or compound concentration data can be loaded from file(s) (in CSV, TSV, or Excel formats), or the user can directly enter individual compounds/genes (using KEGG compound IDs or Entrez Gene IDs) to build metabolic networks without loading a file. MetScape uses an internal relational database that integrates data from KEGG and EHMN.


CorrelationCalculator v1.0.1, featuring a revamped interface, is now available.
MetScape v3.1.3, for use with Cytoscape 3.4.0 and higher, is now available.

New in MetScape 3.1

MetScape 3.1 supports building and visualization of correlation networks, in addition to pathway networks. We developed a new method that uses a Debiased Sparse Partial Correlation (DSPC) algorithm to identify connectivity among large numbers of metabolites using fewer samples. DSPC is implemented as part of our CorrelationCalculator program. DSPC was developed in collaboration with George Michailidis and Sumanta Basu.

MetScape Workflow

Metscape 3 overview diagram

Cite Metscape

Pathway-based networks:

Karnovsky A, Weymouth T, Hull T, Tarcea VG, Scardoni G, Laudanna C, Sartor MA, Stringer KA, Jagadish HV, Burant C, Athey B, Omenn GS.
Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data.
Bioinformatics. 2011 Nov 30

Correlation-based networks:

Basu S, Duren W, Evans CR, Burant C, Michailidis G, Karnovsky A.
Sparse network modeling and Metscape-based visualization methods for the analysis of large-scale metabolomics data.
Bioinformatics. 2017 Jan 30