Department of Mathematics
SKM-SNP: SNP markers detection method
SKM-SNP, SNP markers detection program, is proposed to identify a set of relevant SNPs for the association between a disease and multiple marker genotypes. We employ a subspace categorical clustering algorithm to compute a weight for each SNP in the group of patient samples and the group of normal samples, and use the weights to identify the subsets of relevant SNPs that categorize these two groups. The experiments on both Schizophrenia and Parkinson Disease data sets containing genome-wide SNPs are reported to demonstrate the program. Results indicate that our method can find some relevant SNPs that categorize the disease samples. The online SKM-SNP program is available at http://www.math.hkbu.edu.hk/~mng/SKM-SNP/SKM-SNP.html. © 2009 Elsevier Inc. All rights reserved.
K-mode, Single nucleotide polymorphism, SKM-SNP, Subspace clustering
Source Publication Title
Journal of Biomedical Informatics
Liu, Yang, Mark Li, Yiu M. Cheung, Pak C. Sham, and Michael K. Ng. "SKM-SNP: SNP markers detection method." Journal of Biomedical Informatics 43.2 (2010): 233-239.