Variable-selection ANOVA Simultaneous Component Analysis (VASCA).

ABSTRACT:

Motivation

ANOVA Simultaneous Component Analysis (ASCA) is a popular method for the analysis of multivariate data yielded by designed experiments. Meaningful associations between factors/interactions of the experimental design and measured variables in the dataset are typically identified via significance testing, with permutation tests being the standard go-to choice. However, in settings with large numbers of variables, like omics (genomics, transcriptomics, proteomics and metabolomics) experiments, the 'holistic' testing approach of ASCA (all variables considered) often overlooks statistically significant effects encoded by only a few variables (biomarkers).

Results

We hereby propose Variable-selection ASCA (VASCA), a method that generalizes ASCA through variable selectio

SUBMITTER: Camacho J 

PROVIDER: S-EPMC9825241 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature