gkmSVM: an R package for gapped-kmer SVM.

Journal: Bioinformatics (Oxford, England)
Published Date: Apr 19, 2016

Abstract

UNLABELLED: We present a new R package for training gapped-kmer SVM classifiers for DNA and protein sequences. We describe an improved algorithm for kernel matrix calculation that speeds run time by about 2 to 5-fold over our original gkmSVM algorithm. This package supports several sequence kernels, including: gkmSVM, kmer-SVM, mismatch kernel and wildcard kernel.

Authors

  • Mahmoud Ghandi
    The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Morteza Mohammad-Noori
    School of Mathematics, Statistics, and Computer Science, College of Science, University of Tehran, Tehran, Iran.
  • Narges Ghareghani
    Department of Engineering Science, College of Engineering, University of Tehran, and Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
  • Dongwon Lee
    McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
  • Levi Garraway
    The Broad Institute of MIT and Harvard, Cambridge, MA, USA Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Michael A Beer
    McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

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