Multiple testing and its applications to microarrays
Yongchao Ge, Stuart C Sealfon, Terence P Speed
STATISTICAL METHODS IN MEDICAL RESEARCH | SAGE PUBLICATIONS LTD | Published : 2009
The large-scale multiple testing problems resulting from the measurement of thousands of genes in microarray experiments have received increasing interest during the past several years. This article describes some commonly used criteria for controlling false positive errors, including familywise error rates, false discovery rates and false discovery proportion rates. Various statistical methods controlling these error rates are described. The advantages and disadvantages of these methods are discussed. These methods are applied to gene expression data from two microarray studies and the properties of these multiple testing procedures are compared.
Awarded by NIH
Awarded by NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES
Awarded by NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
We thank Xiaochun Li and Chi-Hong Tseng for their valuable comments on the manuscript. We thank the editors for helpful comments that have led to an improved article. This work was supported by NIH grants U19 AI 62623, RO1 DK46943 and contract HHSN 26600500021C.