Principal interactions analysis for repeated measures data: application to gene-gene and gene-environment interactions.

ABSTRACT: Many existing cohorts with longitudinal data on environmental exposures, occupational history, lifestyle/ behavioral characteristics, and health outcomes have collected genetic data in recent years. In this paper, we consider the problem of modeling gene-gene and gene-environment interactions with repeated measures data on a quantitative trait. We review possibilities of using classical models proposed by Tukey (1949) and Mandel (1961) using the cell means of a two-way classification array for such data. Although these models are effective for detecting interactions in the presence of main effects, they fail miserably if the interaction structure is misspecified. We explore a more robust class of interaction models that are based on a singular value decomposition of the cell-means residual

SUBMITTER: Mukherjee B 

PROVIDER: S-EPMC4046647 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature