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Facilitates an analysis of the metabolomic and transcriptional profiling data in the context of cellular reaction network. GAM service provides a way for a quick interactive analysis of the data to identify the most regulated metabolic subnetworks. The service supports multiple input formats, including results from widely-used DESeq2 and limma pipelines, provides automatic selection of recommended parameter values and uses a range of maximum-weight connected subgraph (MWCS) solvers yielding good suboptimal solutions in a time frame of 30 s.

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GAM classification

GAM specifications

Software type:
Package
Restrictions to use:
None
Output data:
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.
Stability:
Stable
Interface:
Web user interface
Input data:
The analysis takes as input differential expression (DE) tables for genes and/or metabolites between two conditions of interest containing all expressed genes (whether they are differentially expressed or not).
Computer skills:
Basic
Source code URL:
https://github.com/ctlab/shinygam

GAM support

Maintainer

Credits

Publications

Institution(s)

Computer Technologies Department, ITMO University, Saint Petersburg, Russia; Department of Pathology & Immunology, Washington University in St. Louis, St. Louis, MO, USA; Agios Pharmaceuticals, Cambridge, MA, USA; Goodman Cancer Research Centre, McGill University, Montreal, Canada; Department of Physiology, McGill University, Montreal, QC, Canada; General Metabolics, Winchester, MA, USA; Department of Immunometabolism, Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany

Funding source(s)

Supported by Government of Russian Federation [074-U01]

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