TAG SNP SELECTION USING QUINE-McCLUSKEY OPTIMIZATION METHOD

Due to high cost, Genotyping a large number of SNPs is always a challenge for major genome-wide disease association studies. However, depiction in variation of a population can be identified through a very small set of SNPs, known as “Tagging” SNP or “Tag” SNP or “Informative” SNP. Tag SNP is nothing but a small set SNPs selected from the large set which contains the information embedded within them for the whole set. Recent trends of research interest is focused on this retrieval of Tag SNP set. In this paper, we present an efficient Quine McCluskey method for finding such tagging SNPs. Most of the established method for finding Tag SNPs are confined only to localization but the method presented in this paper is not limited to localization and it is also capable of discarding redundant SNPs from the whole set using feature selection (Sliding Window) method. Experimental results shows that the number of Tag SNPs selected by our proposed method is feasible and effective.