Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
Anal Chem. 2006 Jan 15;78(2):567-74.

Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation.

Author information

  • 1Business Unit Analytical Sciences and Business Unit Physiological Sciences, TNO Quality of Life, P.O. Box 360, 3700 AJ Zeist, The Netherlands. bijlsma@voeding.tno.nl

Abstract

A large metabolomics study was performed on 600 plasma samples taken at four time points before and after a single intake of a high fat test meal by obese and lean subjects. All samples were analyzed by a liquid chromatography-mass spectrometry (LC-MS) lipidomic method for metabolic profiling. A pragmatic approach combining several well-established statistical methods was developed for processing this large data set in order to detect small differences in metabolic profiles in combination with a large biological variation. Such metabolomics studies require a careful analytical and statistical protocol. The strategy included data preprocessing, data analysis, and validation of statistical models. After several data preprocessing steps, partial least-squares discriminant analysis (PLS-DA) was used for finding biomarkers. To validate the found biomarkers statistically, the PLS-DA models were validated by means of a permutation test, biomarker models, and noninformative models. Univariate plots of potential biomarkers were used to obtain insight in up- or downregulation. The strategy proposed proved to be applicable for dealing with large-scale human metabolomics studies.

PMID:
16408941
[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for American Chemical Society
    Loading ...
    Write to the Help Desk