GkmSVM: An R package for gapped-kmer SVM

Mahmoud Ghandi; Morteza Mohammad-Noori; Narges Ghareghani; Dongwon Lee; Levi Garraway; Michael A. Beer

doi:10.1093/bioinformatics/btw203

GkmSVM: An R package for gapped-kmer SVM

Mahmoud Ghandi, Morteza Mohammad-Noori, Narges Ghareghani, Dongwon Lee, Levi Garraway, Michael A. Beer

School of Medicine

Research output: Contribution to journal › Article › peer-review

48 Scopus citations

Abstract

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: or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

Original language	English (US)
Pages (from-to)	2205-2207
Number of pages	3
Journal	Bioinformatics
Volume	32
Issue number	14
DOIs	https://doi.org/10.1093/bioinformatics/btw203
State	Published - Jul 15 2016

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btw203

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abstract = "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: or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.",

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AU - Garraway, Levi

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GkmSVM: An R package for gapped-kmer SVM

Abstract

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