More than 6 million single nucleotide polymorphisms (SNPs) in the human genome have been genotyped by the HapMap project. Although only a pro portion of these SNPs are functional, all can be considered as candidate markers for indirect association studies to detect disease-related genetic variants. The complete screening of a gene or a chromosomal region is nevertheless an expensive undertak ing for association studies. A key strategy for improving the efficiency of association studies is to select a subset of informative SNPs, called tag SNPs, for analysis. In the chapter, hierarchical clustering algorithms have been proposed for efficient tag SNP selection.
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Ao, SI. (2009). CLUSTAG & WCLUSTAG: Hierarchical Clustering Algorithms for Efficient Tag-SNP Selection. In: Ao, SI., Rieger, B., Chen, SS. (eds) Advances in Computational Algorithms and Data Analysis. Lecture Notes in Electrical Engineering, vol 14. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8919-0_2
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