title: A design and statistical perspective on microarray gene expression studies in nutrition: the need for playful creativity and scientific hard-mindedness.
abstract: OBJECTIVE
  Our purpose is to highlight some of the past and potential future uses of microarray in nutrition research, while also commenting on some aspects of the design conduct and analysis of microarray data that will leave to improved data quality.
  
  
  METHODS
  In this review article we outline some of the aspects of microarray experimentation that must be considered before and during these experiments. These topics include: identification of the experiment's objective (hypothesis), the experimental design, sample size, statistical analysis, data verification, data handling, and experimental interpretation.
  
  
  RESULTS
  In order to illustrate the principles we outline in this article we use the methods to layout the design of a microarray experiment to study one aspect of the observation that a diet high in soy is associated with lower rates of breast cancer.
  
  
  CONCLUSIONS
  Microarrays are a very powerful tool for studying virtually every nutrition-related disease and trait and can provide valuable insights that are not obtainable with other techniques. However, unless nutrition researchers conduct their studies with scientific hard-mindedness, the studies will be of lower power at least if not completely misleading.
authors: Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama 35294-0022, USA. gpage@ms.soph.uab.edu
authors: Grier P
authors: GP
authors: Page
authors: Jode W
authors: JW
authors: Edwards
authors: Stephen
authors: S
authors: Barnes
authors: Richard
authors: R
authors: Weindruch
authors: David B
authors: DB
authors: Allison
mesh_terms: D000818:Animals; D001943:Breast Neoplasms / Q000453:epidemiology / Q000517:prevention & control; D004032:Diet; D006801:Humans; D009747:Nutritional Physiological Phenomena; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000706:statistics & numerical data*; D012107:Research Design; D013025:Glycine max