title: MetaNetwork: a computational protocol for the genetic study of metabolic networks.
abstract: We here describe the MetaNetwork protocol to reconstruct metabolic networks using metabolite abundance data from segregating populations. MetaNetwork maps metabolite quantitative trait loci (mQTLs) underlying variation in metabolite abundance in individuals of a segregating population using a two-part model to account for the often observed spike in the distribution of metabolite abundance data. MetaNetwork predicts and visualizes potential associations between metabolites using correlations of mQTL profiles, rather than of abundance profiles. Simulation and permutation procedures are used to assess statistical significance. Analysis of about 20 metabolite mass peaks from a mass spectrometer takes a few minutes on a desktop computer. Analysis of 2,000 mass peaks will take up to 4 days. In addition, MetaNetwork is able to integrate high-throughput data from subsequent metabolomics, transcriptomics and proteomics experiments in conjunction with traditional phenotypic data. This way MetaNetwork will contribute to a better integration of such data into systems biology.
authors.affiliation: Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, NL-9751 NN Haren, The Netherlands.
authors.forename: Jingyuan
authors.initials: J
authors.lastname: Fu
authors.forename: Morris A
authors.initials: MA
authors.lastname: Swertz
authors.forename: Joost J B
authors.initials: JJ
authors.lastname: Keurentjes
authors.forename: Ritsert C
authors.initials: RC
authors.lastname: Jansen
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D014644:Genetic Variation; D013058:Mass Spectrometry; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological; D040641:Quantitative Trait Loci; D012984:Software; D049490:Systems Biology / Q000379:methods*