The extent of linkage disequilibrium and computational challenges of single nucleotide polymorphisms in genome-wide association studies
Journal
Current Drug Metabolism
Journal Volume
12
Journal Issue
5
Pages
498-506
Date Issued
2011
Author(s)
Abstract
Single Nucleotide Polymorphisms (SNPs) are the most abundant form of genetic variations observed in the human genome. With the advent of high-throughput genotyping arrays and next-generation sequencing (NGS) platforms, tens of millions of SNPs have been uncovered in several human populations. However, the huge amount of SNPs bring new challenges in subsequent analysis. In reality, a number of SNPs may not be genotyped, and non-mutant bases may be falsely reported as SNPs in the microarray and NGS platforms. Furthermore, the identification of disease susceptibility genes are often confounded by numerous SNPs correlated by chance. In this paper, we review existing approaches for calling SNPs using microarrays and next-generation sequencing (NGS) platforms. Methods for measuring linkage disequilibrium (LD) and applications of the LD structure are discussed. Finally, we compare methods for inferring haplotypes from genotypes using microarray and NGS platforms and present the challenges of using SNPs in large-scale association studies. ? 2011 Bentham Science Publishers Ltd.
Subjects
Algorithm; Haplotype; Linkage disequilibrium; Microarray; Next generation sequencing; Single nucleotide polymorphism
SDGs
Other Subjects
algorithm; article; computer program; DNA microarray; gene identification; gene linkage disequilibrium; genetic association; genetic variability; genotype; haplotype; human; human genome; microarray analysis; single nucleotide polymorphism; Genome-Wide Association Study; Genotype; Haplotypes; Humans; Linkage Disequilibrium; Models, Statistical; Oligonucleotide Array Sequence Analysis; Polymorphism, Single Nucleotide
Type
journal article