gkmSVM: an R package for gapped-kmer SVM.

Bioinformatics
Authors
Mahmoud Ghandi
Morteza Mohammad-Noori
Narges Ghareghani
Dongwon Lee
Levi Garraway
Michael Beer
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.

AVAILABILITY AND IMPLEMENTATION: gkmSVM package is freely available through the Comprehensive R Archive Network (CRAN), for Linux, Mac OS and Windows platforms. The C ++ implementation is available at www.beerlab.org/gkmsvm

CONTACT: mghandi@gmail.com or mbeer@jhu.edu

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Year of Publication
2016
Journal
Bioinformatics
Volume
32
Issue
14
Pages
2205-7
Date Published
2016 Jul 15
ISSN
1367-4811
URL
http://bioinformatics.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=27153639
DOI
10.1093/bioinformatics/btw203
PubMed ID
27153639
PubMed Central ID
PMC4937197
Links
Grant list
R01 HG007348 / HG / NHGRI NIH HHS / United States

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