title: The multivariate nonparametric methods for identifying gene sets with differential expression.
abstract: BACKGROUND
  Gene Set Analysis (GSA) identifies differential expression gene sets amid the different phenotypes. The results of published papers in this filed are inconsistent and there is no consensus on the best method. In this paper two new methods, in comparison to the previous ones, are introduced for GSA.
  
  
  METHODS
  The MMGSA and MRGSA methods based on multivariate nonparametric techniques were presented. The implementation of five GSA methods (Hotelling's T(2), Globaltest, Abs_Cat, Med_Cat and Rs_Cat) and the novel methods to detect differential gene expression between phenotypes were compared using simulated and real microarray data sets.
  
  
  RESULTS
  In a real dataset, the results showed that the powers of MMGSA and MRGSA were as well as Globaltest and Tsai. The MRGSA method has not a good performance in the simulation dataset.
  
  
  CONCLUSIONS
  The Globaltest method is the best method in the real or simulation datasets. The performance of MMGSA in simulation dataset is good in small-size gene sets. The GLS methods are not good in the simulated data, except the Med_Cat method in large-size gene sets.
authors.affiliation: Faculty of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
authors.forename: Soheila
authors.initials: S
authors.lastname: Khodakarim
authors.affiliation: Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
authors.forename: Seyyed Mohammad
authors.initials: SM
authors.lastname: Tabatabaei
authors.affiliation: Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Electronic address: Alavimajd@gmail.com.
authors.forename: Hamid
authors.initials: H
authors.lastname: AlaviMajd
mesh_terms: D030541:Databases, Genetic; D015870:Gene Expression / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D010641:Phenotype; D011471:Prostatic Neoplasms / Q000235:genetics
keywords: Gene set analysis; MMGSA; MRGSA