title: Rgtsp: a generalized top scoring pairs package for class prediction.
abstract: CONCLUSIONS
  A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance.
  
  
  METHODS
  Full C++ source code and R package Rgtsp are freely available from http://lausanne.isb-sib.ch/~vpopovic/research/. The implementation relies on existing OpenMP libraries.
authors.affiliation: Bioinformatics Core Facility, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland. vlad.popovici@isb-sib.ch
authors.forename: Vlad
authors.initials: V
authors.lastname: Popovici
authors.forename: Eva
authors.initials: E
authors.lastname: Budinská
authors.forename: Mauro
authors.initials: M
authors.lastname: Delorenzi
mesh_terms: D002965:Classification / Q000379:methods; D020869:Gene Expression Profiling / Q000379:methods*; D011960:Receptors, Estrogen / Q000378:metabolism; D012984:Software
chemical_list: D011960:Receptors, Estrogen