OBJECTIVES: 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.
OBJECTIVES: 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: Staffan Persson; Hairong Wei; Jennifer Milne; Grier P Page; Christopher R Somerville Journal: Proc Natl Acad Sci U S A Date: 2005-06-02 Impact factor: 11.205
Authors: Stanislav O Zakharkin; Kyoungmi Kim; Tapan Mehta; Lang Chen; Stephen Barnes; Katherine E Scheirer; Rudolph S Parrish; David B Allison; Grier P Page Journal: BMC Bioinformatics Date: 2005-08-29 Impact factor: 3.169
Authors: Grier P Page; Jode W Edwards; Gary L Gadbury; Prashanth Yelisetti; Jelai Wang; Prinal Trivedi; David B Allison Journal: BMC Bioinformatics Date: 2006-02-22 Impact factor: 3.169
Authors: Leming Shi; Weida Tong; Hong Fang; Uwe Scherf; Jing Han; Raj K Puri; Felix W Frueh; Federico M Goodsaid; Lei Guo; Zhenqiang Su; Tao Han; James C Fuscoe; Z Alex Xu; Tucker A Patterson; Huixiao Hong; Qian Xie; Roger G Perkins; James J Chen; Daniel A Casciano Journal: BMC Bioinformatics Date: 2005-07-15 Impact factor: 3.169