Genome-Wide Association Studies (GWAS) consider the Linkage Disequilibrium (LD) structure of a genome in order to use the genetic markers more efficiently. This property of single-nucleotide polymorphisms (SNPs) on a neighboring part of a genomic sequence describes the degree to which an allele of one SNP is correlated with an allele of another SNP in a population. Mathematically, LD describes the genetic variation for a population over time. LD optimizes the genetic association studies by identifying the tag SNPs that prevents genotyping of SNPs which provide redundant information. Hence, accurate specification of LD structures is a crucial to enhance the genetic studies. Many measures of LD have been proposed. One of the most commonly used measures for LD is the pairwise-r^2. This paper provides how different LD features can be extracted from SNP genotype data using the pairwise-r^2.
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