The International HapMap Project

@article{Tanaka2003TheIH,
  title={The International HapMap Project},
  author={Toshihiro Tanaka},
  journal={Nature},
  year={2003},
  volume={426},
  pages={789-796}
}
The goal of the International HapMap Project is to determine the common patterns of DNA sequence variation in the human genome and to make this information freely available in the public domain. [] Key Method An international consortium is developing a map of these patterns across the genome by determining the genotypes of one million or more sequence variants, their frequencies and the degree of association between them, in DNA samples from populations with ancestry from parts of Africa, Asia and Europe…
Perspectives on Human Genetic Variation from the HapMap Project
TLDR
What the HapMap project has taught us about the structure of human genetic variation and the fundamental molecular and evolutionary processes that shape it is focused on.
A HapMap harvest of insights into the genetics of common disease.
TLDR
HapMap-based discoveries have shed new light on the impact of evolutionary pressures on the human genome, suggesting multiple loci important for adapting to disease-causing pathogens and new environments.
Beyond the HapMap Genotypic Data: Prospects of Deep Resequencing Projects.
TLDR
Three large-scale deep resequencing projects covering the HapMap samples: ENCODE, SeattleSNPs and NIEHS (National Institute of Environmental Health Sciences) Environmental Genome Project are discussed and it is suggested that these efforts will greatly benefit the next wave of association studies and data mining using these cell lines.
Sequencing Complex Diseases With HapMap
TLDR
A novel statistical model for directly characterizing specific sequence variants that are responsible for disease risk based on the haplotype structure provided by HapMap is presented, developed in the maximum-likelihood context, implemented with the EM algorithm.
Navigating the HapMap
TLDR
This review will examine tools for viewing and analysing haplotype and LD data, enabling a number of tasks; including identification of optimal sets of haplotype tagging single nucleotide polymorphisms (SNPs); drawing links between associated SNPs and putative causal alleles; or simply viewing LD and haplotypes across a gene or region of interest.
The HapMap Resource is Providing New Insights into Ourselves and its Application to Pharmacogenomics
TLDR
The HapMap Project provides new insights into the human genome and has applicability to pharmacogenomics studies leading to personalized medicine.
The HapMap and genome-wide association studies in diagnosis and therapy.
TLDR
The development and application of the HapMap to genome-wide association (GWA) studies; present and future technologies for GWA research; current major efforts in GWA studies; successes and limitations of the GWA approach in identifying polymorphisms related to complex diseases; data release and privacy polices; and sources of ongoing authoritative information on this rapidly evolving field are examined.
How well do HapMap SNPs capture the untyped SNPs?
TLDR
HapMap SNPs cannot capture some of the untyped SNPs and therefore resequencing may be needed to uncover more SNPs in the missing region, and the results show that HapMapSNPs are transferable to the NIEHS SNPs.
A pharmacogene database enhanced by the 1000 Genomes Project.
TLDR
A new database of some pharmacogenes of particular interest to pharmacogenetic researchers is presented, which provides a convenient portal for immediate utilization of the newly released 1000 Genomes Project data in pharmacogenetics studies.
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