title: Cancer outlier detection based on likelihood ratio test.
abstract: BACKGROUND
  Microarray experiments can be used to help study the role of chromosomal translocation in cancer development through cancer outlier detection. The aim is to identify genes that are up- or down-regulated in a subset of cancer samples in comparison to normal samples.
  
  
  RESULTS
  We propose a likelihood-based approach which targets detecting the change of point in mean expression intensity in the group of cancer samples. A desirable property of the proposed approach is the availability of theoretical significance-level results. Simulation studies showed that the performance of the proposed approach is appealing in terms of both detection power and false discovery rate. And the real data example also favored the likelihood-based approach in terms of the biological relevance of the results.
  
  
  BACKGROUND
  R code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/~jhhu/cod-analysis/.
authors.affiliation: Department of Biostatistics, Division of Quantitative Science, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA. jhu@mdanderson.org
authors.forename: Jianhua
authors.initials: J
authors.lastname: Hu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005189:False Positive Reactions; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D016013:Likelihood Functions; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis