publication . Article . 2006

Haplotype-based quantitative trait mapping using a clustering algorithm

Jing Li; Yingyao Zhou; Robert C Elston;
Open Access English
  • Published: 01 May 2006 Journal: BMC Bioinformatics, volume 7, pages 258-258 (eissn: 1471-2105, Copyright policy)
  • Publisher: BioMed Central
Abstract
<p>Abstract</p> <p>Background</p> <p>With the availability of large-scale, high-density single-nucleotide polymorphism (SNP) markers, substantial effort has been made in identifying disease-causing genes using linkage disequilibrium (LD) mapping by haplotype analysis of unrelated individuals. In addition to complex diseases, many continuously distributed quantitative traits are of primary clinical and health significance. However the development of association mapping methods using unrelated individuals for quantitative traits has received relatively less attention.</p> <p>Results</p> <p>We recently developed an association mapping method for complex diseases by...
Subjects
free text keywords: Methodology Article, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5, Biochemistry, Applied Mathematics, Molecular Biology, Structural Biology, Computer Science Applications, Bioinformatics, Association mapping, Linkage disequilibrium, Tag SNP, Haplotype, Genetics, Polymorphism (computer science), Quantitative trait locus, Cluster analysis, Biology, SNP
Funded by
NIH| Multi-point and multi-locus analysis of genomic association data
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01LM008991-05
  • Funding stream: NATIONAL LIBRARY OF MEDICINE
,
NIH| Linkage Consortium End-Stage-Renal Disease
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5U01DK057292-09
  • Funding stream: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
,
NIH| Case Comprehensive Cancer Center Support Grant
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 3P30CA043703-20S1
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NSF| Sublinear Property Testing of Large Collections of Data Objects
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 0311548
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Computing and Communication Foundations
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