Robust detection and verification of linear relationships to generate metabolic networks using estimates of technical errors

Background: The size and magnitude of the metabolome, the ratio between individual metabolites and the response of metabolic networks is controlled by multiple cellular factors. A tight control over metabolite ratios will be reflected by a linear relationship of pairs of metabolite due to the flexibility of metabolic pathways. Hence, unbiased detection and validation of linear metabolic variance can be interpreted in terms of biological control. For robust analyses, criteria for rejecting or accepting linearities need to be developed despite technical measurement errors. The entirety of all pair wise linear metabolic relationships then yields insights into the network of cellular regulation. Results: The Bayesian law was applied for detecting linearities that are validated by explaining the residues by the degree of technical measurement errors. Test statistics were developed and the algorithm was tested on simulated data using 3–150 samples and 0–100% technical error. Under the n...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Frank Kose, Jan Budczies, Matthias Holschneider, Oliver Fiehn
• Keywords: BMCBI 2007, Error Rates, Linear Relationships, Technical Measurement Errors