Statistical hypothesis testing of factor loading in principal component analysis and its application to metabolite set enrichment analysis.

ABSTRACT:

Background

Principal component analysis (PCA) has been widely used to visualize high-dimensional metabolomic data in a two- or three-dimensional subspace. In metabolomics, some metabolites (e.g., the top 10 metabolites) have been subjectively selected when using factor loading in PCA, and biological inferences are made for these metabolites. However, this approach may lead to biased biological inferences because these metabolites are not objectively selected with statistical criteria.

Results

We propose a statistical procedure that selects metabolites with statistical hypothesis testing of the factor loading in PCA and makes biological inferences about these significant metabolites with a metabolite set enrichment analysis (MSEA). This procedure depends on the fact that the

SUBMITTER: Yamamoto H 

PROVIDER: S-EPMC4015128 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature