Exploring dynamic metabolomics data with multiway data analysis: a simulation study.

ABSTRACT:

Background

Analysis of dynamic metabolomics data holds the promise to improve our understanding of underlying mechanisms in metabolism. For example, it may detect changes in metabolism due to the onset of a disease. Dynamic or time-resolved metabolomics data can be arranged as a three-way array with entries organized according to a subjects mode, a metabolites mode and a time mode. While such time-evolving multiway data sets are increasingly collected, revealing the underlying mechanisms and their dynamics from such data remains challenging. For such data, one of the complexities is the presence of a superposition of several sources of variation: induced variation (due to experimental conditions or inborn errors), individual variation, and measurement error. Multiway data analysis

SUBMITTER: Li L 

PROVIDER: S-EPMC8750750 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature