title: A gene selection method for GeneChip array data with small sample sizes.
abstract: BACKGROUND
  In microarray experiments with small sample sizes, it is a challenge to estimate p-values accurately and decide cutoff p-values for gene selection appropriately. Although permutation-based methods have proved to have greater sensitivity and specificity than the regular t-test, their p-values are highly discrete due to the limited number of permutations available in very small sample sizes. Furthermore, estimated permutation-based p-values for true nulls are highly correlated and not uniformly distributed between zero and one, making it difficult to use current false discovery rate (FDR)-controlling methods.
  
  
  RESULTS
  We propose a model-based information sharing method (MBIS) that, after an appropriate data transformation, utilizes information shared among genes. We use a normal distribution to model the mean differences of true nulls across two experimental conditions. The parameters of the model are then estimated using all data in hand. Based on this model, p-values, which are uniformly distributed from true nulls, are calculated. Then, since FDR-controlling methods are generally not well suited to microarray data with very small sample sizes, we select genes for a given cutoff p-value and then estimate the false discovery rate.
  
  
  CONCLUSIONS
  Simulation studies and analysis using real microarray data show that the proposed method, MBIS, is more powerful and reliable than current methods. It has wide application to a variety of situations.
authors.affiliation: Biostatistics Epidemiology Research Design Core, Center for Clinical and Translational Sciences, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA. Zhongxue.Chen@uth.tmc.edu
authors.forename: Zhongxue
authors.initials: Z
authors.lastname: Chen
authors.forename: Qingzhong
authors.initials: Q
authors.lastname: Liu
authors.forename: Monnie
authors.initials: M
authors.lastname: McGee
authors.forename: Megan
authors.initials: M
authors.lastname: Kong
authors.forename: Xudong
authors.initials: X
authors.lastname: Huang
authors.forename: Youping
authors.initials: Y
authors.lastname: Deng
authors.forename: Richard H
authors.initials: RH
authors.lastname: Scheuermann
mesh_terms: D000465:Algorithms; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D012372:ROC Curve