Variable selection in omics data: A practical evaluation of small sample sizes.

ABSTRACT: In omics experiments, variable selection involves a large number of metabolites/ genes and a small number of samples (the n < p problem). The ultimate goal is often the identification of one, or a few features that are different among conditions- a biomarker. Complicating biomarker identification, the p variables often contain a correlation structure due to the biology of the experiment making identifying causal compounds from correlated compounds difficult. Additionally, there may be elements in the experimental design (blocks, batches) that introduce structure in the data. While this problem has been discussed in the literature and various strategies proposed, the over fitting problems concomitant with such approaches are rarely acknowledged. Instead of viewing a single omics experiment

SUBMITTER: Kirpich A 

PROVIDER: S-EPMC6013185 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature