Open Access Highly Accessed Research article

MetaMapp: mapping and visualizing metabolomic data by integrating information from biochemical pathways and chemical and mass spectral similarity

Dinesh K Barupal1, Pradeep K Haldiya1, Gert Wohlgemuth1, Tobias Kind1, Shanker L Kothari3, Kent E Pinkerton2 and Oliver Fiehn1*

Author Affiliations

1 UC Davis Genome Center, Metabolomics, Davis, 95616, CA, USA

2 UC Davis Center for Health and the Environmental, Davis, 95616, CA, USA

3 DBT-Bioinformatics Infrastructure Facility, University of Rajasthan, Jaipur, India

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BMC Bioinformatics 2012, 13:99  doi:10.1186/1471-2105-13-99

Published: 16 May 2012

Additional files

Additional file 1 :

Table S1. Results of Analysis of variance (ANOVA) for all 459 metabolites detected in the rat environmental tobacco smoke exposure study, compliant to MSI-recommendations (Metabolomics standard including international chemical identifier keys (InChI), PubChem and KEGG database identifiers and retention index and quantification ion information. ETS = Environmental Tobacco smoke exposed, FA = filtered air exposed.

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Additional file 2 :

Table S2. Bioinformatics databases that were queried for identified metabolites.

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Additional file 3 :

Table S3. A list of web tools for pathway mapping analysis of a list of metabolites associated with KEGG or PubChem Identifiers.

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Additional file 4 :

Figure S4. KEGG Atlas Global Map visualization. Mapped metabolites are highlighted as black nodes yielding an overall sparse coverage of the graph. 45% of the identified metabolites in the rat ETS study were not covered by the KEGG Atlas Global Map.

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Additional file 5 :

Figure S5. Mapping the 179 identified metabolites of the rat ETS study on biochemical network graphs using various publicly available tools and databases. See method section for details on construction of these graphs. (a) Edinburgh human metabolic network; (b) HumanCyc; (c) Reactome; (d) BIGG-UCSD; (e) KEGG RPAIR network; (f) MetaCyc reaction DB; (g) Cytoscape network using only the 137 metabolites retrieved from the KEGG pathway repository; (g) Cytoscape network of the 137 metabolites retrieved from the KEGG pathway on all metabolites comprised in the KEGG pathway repository.

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Additional file 6 :

Figure S6. Impact of Tanimoto chemical similarity thresholds on visual appearance and clarity of metabolomic networks in Cytoscape without addition of KEGG reactant pair information. Nodes are metabolites and edges are chemical similarity links. (a) Network without any similarity threshold; (b) using a Tanimoto threshold of 0.9; (c) using a Tanimoto threshold of 0.8; (d) using a Tanimoto threshold of 0.7; (e) using a Tanimoto threshold of 0.6; (f) using a Tanimoto threshold of 0.5; (g) linking all metabolites to the two most Tanimoto-similar compounds; (h) combining data matrices from networks (d) and (g).

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Additional file 7 :

Figure S7. A MetaMapp network graph displaying labels for all the identified metabolites. Nodes are metabolites, red edges are KEGG RPAIR links and blue edges denote chemical similarity links.

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Additional file 8 :

S8. A zip file containing the input Tanimoto chemical similarity matrix, ANOVA output, KEGG Ids, CID pairs and Cytoscape session files for all 179 identified metabolites. The session files can be opened directly into Cytoscape.

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