Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06) (2006)
Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.43
Michael K. Ng , Hong Kong Baptist University
Mark J. Li , Hong Kong Baptist University
Sio I. Ao , Hong Kong Baptist University
Pak C. Sham , University of Hong Kong
Yiu-ming Cheung , Hong Kong Baptist University
Joshua Z. Huang , University of Hong Kong
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.
M. K. Ng, Y. Cheung, M. J. Li, S. I. Ao, J. Z. Huang and P. C. Sham, "Clustering of SNP Data with Application to Genomics," Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)(ICDMW), Hong Kong, China, 2006, pp. 158-162.