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- Stacey B. Gabriel
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Stephen F. Schaffner
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Huy Nguyen
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Jamie M. Moore
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Jessica Roy
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Brendan Blumenstiel
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- John Higgins
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Matthew DeFelice
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Amy Lochner
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Maura Faggart
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Shau Neen Liu-Cordero
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Charles Rotimi
- National Human Genome Center, Howard University, Washington, DC 20059, USA.
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- Adebowale Adeyemo
- Department of Pediatrics, College of Medicine, University of Ibadan, Ibadan, Nigeria.
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- Richard Cooper
- Department of Preventive Medicine and Epidemiology, Loyola University Medical School, Maywood, IL 60143, USA.
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- Ryk Ward
- Institute of Biological Anthropology, University of Oxford, Oxford, England OX2 6QS.
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- Eric S. Lander
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- Mark J. Daly
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
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- David Altshuler
- Whitehead/MIT Center for Genome Research, Cambridge, MA 02139, USA.
説明
<jats:p>Haplotype-based methods offer a powerful approach to disease gene mapping, based on the association between causal mutations and the ancestral haplotypes on which they arose. As part of The SNP Consortium Allele Frequency Projects, we characterized haplotype patterns across 51 autosomal regions (spanning 13 megabases of the human genome) in samples from Africa, Europe, and Asia. We show that the human genome can be parsed objectively into haplotype blocks: sizable regions over which there is little evidence for historical recombination and within which only a few common haplotypes are observed. The boundaries of blocks and specific haplotypes they contain are highly correlated across populations. We demonstrate that such haplotype frameworks provide substantial statistical power in association studies of common genetic variation across each region. Our results provide a foundation for the construction of a haplotype map of the human genome, facilitating comprehensive genetic association studies of human disease.</jats:p>
収録刊行物
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- Science
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Science 296 (5576), 2225-2229, 2002-06-21
American Association for the Advancement of Science (AAAS)
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詳細情報 詳細情報について
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- CRID
- 1360855567863188864
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- NII論文ID
- 80015380572
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- ISSN
- 10959203
- 00368075
- http://id.crossref.org/issn/00368075
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- データソース種別
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- Crossref
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