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R/DWD | Distance-weighted discrimination for classification, visualization and batch adjustment


Provides the implementation of distance weighted discrimination (DWD) using an interior point method for the solution of second order cone programming problems. 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.

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R/DWD classification

R/DWD specifications

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Command line interface
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Unix/Linux, Mac OS, Windows
GNU General Public License version 2.0
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R/DWD support


  • Hanwen Huang <>


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Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Funding source(s)

Grant number NIH/NCI R01 CA-149569

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