Global and Partial Effect Assessment in Metabolic Syndrome Explored by Metabolomics.

ABSTRACT: In nutrition and health research, untargeted metabolomics is actually analyzed simultaneously with clinical data to improve prediction and better understand pathological status. This can be modeled using a multiblock supervised model with several input data blocks (metabolomics, clinical data) being potential predictors of the outcome to be explained. Alternatively, this configuration can be represented with a path diagram where the input blocks are each connected by links directed to the outcome-as in multiblock supervised modeling-and are also related to each other, thus allowing one to account for block effects. On the basis of a path model, we show herein how to estimate the effect of an input block, either on its own or conditionally to other(s), on the output response, respectively c

SUBMITTER: Brandolini-Bunlon M 

PROVIDER: S-EPMC10058487 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature