Data analysis strategies in nutritional metabolomics

In the expanding field of nutritional metabolomics the use of optimized and robust strategies are essential to find meaningful and significant results. Data from nutritional studies can be extremely large, multidimensional and complex. Moreover the data may hide just a subtle biological variation due to the nutritional treatment, and the effect may be highly variable across individuals. Usually the treatment effects are much smaller than the biological variations between individuals. A properly chosen experimental design and a well-adapted data analysis strategy are therefore essential to ensure that the intended information in the data can be assessed and that the biological question of interest can be answered.