MetaMapR

Version: 1.2.1

Website

http://dgrapov.github.io/MetaMapR/

Description

MetaMapR uses structural similarity, mass spectral similarity and empirical correlation information to generate metabolic networks from metabolomics data. It is able to fill in the missing gaps in the network using this extra biochemical information. Data can be inputted in over 200 biological database identifiers as the package CTSgetR is used to translate between different common chemical databases (CTSgetR is an R package which interfaces with the chemical translation system (CTS)). Optionally m/z and intensity pair strings can be uploaded to calculate empirical correlation relationships. Metabolites can be mapped to KEGG or PubChem CIDs to calculate biochemical similarity networks. Reaction networks are generated using substrate-product pair reactions from the KEGG RPAIR. PubChem substructure fingerprints are used to generate structural similarity networks using Tanimoto similarity. Cosine correlations are calculated pairwise between mass spectra to obtain the spectral similarity score. Pearson, biweight correlations and Spearman correlations between measure metabolite values are calculated to obtain empirical dependency networks. Results can then be exported to cytoscape.

Functionality

• Pathway Analysis

Instrument Data Type

Approaches

Computer Skills

• Medium
• Advanced

Software Type

• Web App
• R Package

Interface

• Web user interface
• Command line interface

Operating System (OS)

• Unix/Linux
• Mac OS
• Windows

Language

R, Twitter Bootstrap front-end, CSS, HTML, JavaScript

Dependencies

Shiny

Input Formats - Open

Peaklist .csv

Input Formats - Proprietary

N/A

Published

2014

Last Updated

2015

License

GPL-3

Paper

http://www.ncbi.nlm.nih.gov/pubmed/25847005

PMID

25847005