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2013 IEEE 13th International Conference on Data Mining Workshops (2006)
Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
ISBN: 0-7695-2702-7
pp: 158-162
Michael K. Ng , Hong Kong Baptist University
Yiu-ming Cheung , Hong Kong Baptist University
Mark J. Li , Hong Kong Baptist University
Sio I. Ao , Hong Kong Baptist University
Joshua Z. Huang , University of Hong Kong
Pak C. Sham , University of Hong Kong
ABSTRACT
Single nucleotide polymorphisms (SNPs) are very common throughout the genome and hence are potentially valuable for mapping disease susceptibility loci by detecting association between SNP markers and disease. Many methods may only be applicable when marker haplotypes, rather than genotypes (categorical data), are available for analysis. In this paper, we explore the properties of k-modes (categorical data) clustering algorithms to SNP data for detecting association between SNP markers and disease. Subspace k-modes clustering properties are also considered and tested.
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CITATION
Michael K. Ng, Yiu-ming Cheung, Mark J. Li, Sio I. Ao, Joshua Z. Huang, Pak C. Sham, "Clustering of SNP Data with Application to Genomics", 2013 IEEE 13th International Conference on Data Mining Workshops, vol. 00, no. , pp. 158-162, 2006, doi:10.1109/ICDMW.2006.43
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