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GAM: a web-service for integrated transcriptional and metabolic network analysis.


ABSTRACT: Novel techniques for high-throughput steady-state metabolomic profiling yield information about changes of nearly thousands of metabolites. Such metabolomic profiles, when analyzed together with transcriptional profiles, can reveal novel insights about underlying biological processes. While a number of conceptual approaches have been developed for data integration, easily accessible tools for integrated analysis of mammalian steady-state metabolomic and transcriptional data are lacking. Here we present GAM ('genes and metabolites'): a web-service for integrated network analysis of transcriptional and steady-state metabolomic data focused on identification of the most changing metabolic subnetworks between two conditions of interest. In the web-service, we have pre-assembled metabolic networks for humans, mice, Arabidopsis and yeast and adapted exact solvers for an optimal subgraph search to work in the context of these metabolic networks. The output is the most regulated metabolic subnetwork of size controlled by false discovery rate parameters. The subnetworks are then visualized online and also can be downloaded in Cytoscape format for subsequent processing. The web-service is available at: https://artyomovlab.wustl.edu/shiny/gam/.

SUBMITTER: Sergushichev AA 

PROVIDER: S-EPMC4987878 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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GAM: a web-service for integrated transcriptional and metabolic network analysis.

Sergushichev Alexey A AA   Loboda Alexander A AA   Jha Abhishek K AK   Vincent Emma E EE   Driggers Edward M EM   Jones Russell G RG   Pearce Edward J EJ   Artyomov Maxim N MN  

Nucleic acids research 20160420 W1


Novel techniques for high-throughput steady-state metabolomic profiling yield information about changes of nearly thousands of metabolites. Such metabolomic profiles, when analyzed together with transcriptional profiles, can reveal novel insights about underlying biological processes. While a number of conceptual approaches have been developed for data integration, easily accessible tools for integrated analysis of mammalian steady-state metabolomic and transcriptional data are lacking. Here we  ...[more]

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