title: Importance of presenting the variability of the false discovery rate control.
abstract: BACKGROUND
  Multiple hypothesis testing is a pervasive problem in genomic data analysis. The conventional Bonferroni method which controls the family-wise error rate is conservative and with low power. The current paradigm is to control the false discovery rate.
  
  
  RESULTS
  We characterize the variability of the false discovery rate indices (local false discovery rates, q-value and false discovery proportion) using the bootstrapped method. A colon cancer gene-expression data and a visual refractive errors genome-wide association study data are analyzed as demonstration. We found a high variability in false discovery rate controls for typical genomic studies.
  
  
  CONCLUSIONS
  We advise researchers to present the bootstrapped standard errors alongside with the false discovery rate indices.
authors.affiliation: Research Center for Genes, Environment and Human Health and Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Rm. 536, No. 17, Xuzhou Rd., Taipei, 100, Taiwan. timothylin29@hotmail.com.
authors.forename: Yi-Ting
authors.initials: YT
authors.lastname: Lin
authors.affiliation: Research Center for Genes, Environment and Human Health and Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Rm. 536, No. 17, Xuzhou Rd., Taipei, 100, Taiwan. wenchung@ntu.edu.tw.
authors.forename: Wen-Chung
authors.initials: WC
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D003110:Colonic Neoplasms / Q000235:genetics; D055106:Genome-Wide Association Study / Q000379:methods; D006801:Humans; D015233:Models, Statistical