title: High-throughput SNP analysis for genetic association studies.
abstract: Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation, and millions of SNPs are now documented. Because of their dense distribution across the genome, SNPs are viewed as ideal markers for large-scale genome-wide association studies to discover genes in common complex diseases, such as cancer. To enable such studies, researchers have constructed appropriate sets of SNP markers, by selecting SNPs that are common in major human populations and by charting the patterns of co-occurrence of SNPs, which could further guide marker selection. High-throughput SNP analysis technologies have also been developed, which can analyze thousands of SNPs in thousands of samples. As SNP analysis techniques and SNP marker sets are improving, researchers have begun to carry out large-scale genome scans for disease genes, with encouraging first results.
authors.affiliation: Sequenom Inc, Pharmaceuticals Division, 3595 John Hopkins Court, San Diego, CA 92121, USA. gmarnellos@sequenom.com
authors.forename: George
authors.initials: G
authors.lastname: Marnellos
mesh_terms: D000818:Animals; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000639:trends