Clustering of SNP Data with Application to Genomics

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	Similar Articles Articles by Michael K. Ng Articles by Mark J. Li Articles by Sio I. Ao Articles by Pak C. Sham Articles by Yiu-ming Cheung Articles by Joshua Z. Huang

Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)

Hong Kong, China

December 18-December 22

ISBN: 0-7695-2702-7

	ASCII Text	x
	Michael K. Ng, Mark J. Li, Sio I. Ao, Pak C. Sham, Yiu-ming Cheung, Joshua Z. Huang, "Clustering of SNP Data with Application to Genomics," Data Mining Workshops, International Conference on, pp. 158-162, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006.

	BibTex	x
	@article{ 10.1109/ICDMW.2006.43, author = {Michael K. Ng and Mark J. Li and Sio I. Ao and Pak C. Sham and Yiu-ming Cheung and Joshua Z. Huang}, title = {Clustering of SNP Data with Application to Genomics}, journal ={Data Mining Workshops, International Conference on}, volume = {0}, year = {2006}, isbn = {0-7695-2702-7}, pages = {158-162}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.43}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining Workshops, International Conference on TI - Clustering of SNP Data with Application to Genomics SN - 0-7695-2702-7 SP158 EP162 A1 - Michael K. Ng, A1 - Mark J. Li, A1 - Sio I. Ao, A1 - Pak C. Sham, A1 - Yiu-ming Cheung, A1 - Joshua Z. Huang, PY - 2006 KW - null VL - 0 JA - Data Mining Workshops, International Conference on ER -

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

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.43

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.

Citation:

Michael K. Ng, Mark J. Li, Sio I. Ao, Pak C. Sham, Yiu-ming Cheung, Joshua Z. Huang, "Clustering of SNP Data with Application to Genomics," icdmw, pp.158-162, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006

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