The International HapMap Consortium has created a public database of common genetic variation in the human genome, including over one million single nucleotide polymorphisms (SNPs) genotyped in 269 DNA samples from four populations. This data reveals patterns of recombination hotspots, block-like structures of linkage disequilibrium (LD), and low haplotype diversity, leading to strong correlations between SNPs and their neighbors. The HapMap resource helps guide genetic association studies, identify structural variation, and detect loci subject to natural selection. Common genetic variants play a significant role in disease, as evidenced by validated examples such as HLA, APOE4, and PPARG. Linkage disequilibrium (LD) allows for the prediction of alleles at one site based on alleles at nearby sites, forming haplotypes. LD arises from shared ancestry and is influenced by recombination and mutation rates. The HapMap project aims to provide a comprehensive resource for genetic studies, enabling the identification of common variants associated with disease. The HapMap data includes 1,007,329 SNPs, with high accuracy and completeness. These SNPs are evenly spaced across the genome, except on Y and mtDNA. The data includes a common SNP every 5 kb across most of the genome in each analysis panel. The project has two phases: Phase I, which genotyped at least one common SNP every 5 kb across the genome in each of 269 DNA samples, and Phase II, which aims to genotype an additional 4.6 million SNPs in each sample. The HapMap data includes ten 500-kb regions selected from the ENCODE Project, with each region sequenced in 48 individuals and all SNPs genotyped in the complete set of 269 DNA samples. The data includes samples from the Yoruba in Ibadan, Nigeria (YRI), the Centre d'Etude du Polymorphisme Humain collection (CEU), the Han Chinese in Beijing, China (CHB), and the Japanese in Tokyo, Japan (JPT). The data reveals that most SNPs are rare, but most heterozygous sites in individuals are due to common SNPs. The HapMap data shows that haplotypes are often shared across populations, with some haplotypes being unique to certain populations. The data also reveals that recombination rates vary across the genome, with hotspots of recombination explaining much crossing over in each region. The data shows a block-like structure of LD, with segments of consistently high D' breaking where high recombination rates, hotspots, and obligate recombination events cluster. The HapMap data provides a comprehensive resource for genetic studies, enabling the identification of common variants associated with disease. The data includes a large number of SNPs, with high accuracy and completeness. The data reveals that most SNThe International HapMap Consortium has created a public database of common genetic variation in the human genome, including over one million single nucleotide polymorphisms (SNPs) genotyped in 269 DNA samples from four populations. This data reveals patterns of recombination hotspots, block-like structures of linkage disequilibrium (LD), and low haplotype diversity, leading to strong correlations between SNPs and their neighbors. The HapMap resource helps guide genetic association studies, identify structural variation, and detect loci subject to natural selection. Common genetic variants play a significant role in disease, as evidenced by validated examples such as HLA, APOE4, and PPARG. Linkage disequilibrium (LD) allows for the prediction of alleles at one site based on alleles at nearby sites, forming haplotypes. LD arises from shared ancestry and is influenced by recombination and mutation rates. The HapMap project aims to provide a comprehensive resource for genetic studies, enabling the identification of common variants associated with disease. The HapMap data includes 1,007,329 SNPs, with high accuracy and completeness. These SNPs are evenly spaced across the genome, except on Y and mtDNA. The data includes a common SNP every 5 kb across most of the genome in each analysis panel. The project has two phases: Phase I, which genotyped at least one common SNP every 5 kb across the genome in each of 269 DNA samples, and Phase II, which aims to genotype an additional 4.6 million SNPs in each sample. The HapMap data includes ten 500-kb regions selected from the ENCODE Project, with each region sequenced in 48 individuals and all SNPs genotyped in the complete set of 269 DNA samples. The data includes samples from the Yoruba in Ibadan, Nigeria (YRI), the Centre d'Etude du Polymorphisme Humain collection (CEU), the Han Chinese in Beijing, China (CHB), and the Japanese in Tokyo, Japan (JPT). The data reveals that most SNPs are rare, but most heterozygous sites in individuals are due to common SNPs. The HapMap data shows that haplotypes are often shared across populations, with some haplotypes being unique to certain populations. The data also reveals that recombination rates vary across the genome, with hotspots of recombination explaining much crossing over in each region. The data shows a block-like structure of LD, with segments of consistently high D' breaking where high recombination rates, hotspots, and obligate recombination events cluster. The HapMap data provides a comprehensive resource for genetic studies, enabling the identification of common variants associated with disease. The data includes a large number of SNPs, with high accuracy and completeness. The data reveals that most SN