title: R/DWD: distance-weighted discrimination for classification, visualization and batch adjustment.
abstract: R/DWD is an extensible package for classification. It is built based on a recently developed powerful classification method called distance weighted discrimination (DWD). DWD is related to, and has been shown to be superior to, the support vector machine in situations that are fundamental to bioinformatics, such as very high dimensional data. DWD has proven to be very useful for several fundamental bioinformatics tasks, including classification, data visualization and removal of biases, such as batch effects. Earlier DWD implementations, however, relied on Matlab, which is not free and requires a license. The major contribution of the R/DWD package is an implementation that is completely in R and thus can be used without any requirements for licensing or software purchase. In addition, R/DWD also provides efficient solvers for second-order-cone-programming and quadratic programming.
  
  
  METHODS
  The package is freely available from cran.r-project.org.
authors.affiliation: Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. hanwen.huang@uth.tmc.edu
authors.forename: Hanwen
authors.initials: H
authors.lastname: Huang
authors.forename: Xiaosun
authors.initials: X
authors.lastname: Lu
authors.forename: Yufeng
authors.initials: Y
authors.lastname: Liu
authors.forename: Perry
authors.initials: P
authors.lastname: Haaland
authors.forename: J S
authors.initials: JS
authors.lastname: Marron
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012984:Software; D060388:Support Vector Machine