Data analysis of MS-based clinical lipidomics studies with crossover design: A tutorial mini-review of statistical methods.

ABSTRACT: Clinical lipidomics using mass spectrometry (MS) is important to support discovery of biomarkers for diagnosis and understanding the pathophysiology of diseases. Frequently, lipidomics data from clinical studies have large variations among individuals because the human metabolome/lipidome is strongly influenced by genotype, daily activity, diet and gut flora. This inter-personal variability makes data analysis more complex and normally requires a large cohort for robust statistical analysis. Crossover designed experiments treat each subject as his or her own control, thereby reducing the between-subject variability, such that the effects of exposure/treatment are more likely to be identified when using a relatively small number of subjects. This design repeatedly samples an individual when

SUBMITTER: Zhao X 

PROVIDER: S-EPMC8620525 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature