title: Assessing stability of gene selection in microarray data analysis.
abstract: BACKGROUND
  The number of genes declared differentially expressed is a random variable and its variability can be assessed by resampling techniques. Another important stability indicator is the frequency with which a given gene is selected across subsamples. We have conducted studies to assess stability and some other properties of several gene selection procedures with biological and simulated data.
  
  
  RESULTS
  Using resampling techniques we have found that some genes are selected much less frequently (across sub-samples) than other genes with the same adjusted p-values. The extent to which this type of instability manifests itself can be assessed by a method introduced in this paper. The effect of correlation between gene expression levels on the performance of multiple testing procedures is studied by computer simulations.
  
  
  CONCLUSIONS
  Resampling represents a tool for reducing the set of initially selected genes to those with a sufficiently high selection frequency. Using resampling techniques it is also possible to assess variability of different performance indicators. Stability properties of several multiple testing procedures are described at length in the present paper.
authors.affiliation: Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. xqiu@bst.rochester.edu
authors.forename: Xing
authors.initials: X
authors.lastname: Qiu
authors.forename: Yuanhui
authors.initials: Y
authors.lastname: Xiao
authors.forename: Alexander
authors.initials: A
authors.lastname: Gordon
authors.forename: Andrei
authors.initials: A
authors.lastname: Yakovlev
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics*; D002648:Child; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods*; D014644:Genetic Variation; D006801:Humans; D007938:Leukemia / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D009363:Neoplasm Proteins / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins