4.3 Article Proceedings Paper

Summary of Genetic Analysis Workshop 15: Group 9 linkage analysis of the CEPH expression data

期刊

GENETIC EPIDEMIOLOGY
卷 31, 期 -, 页码 S75-S85

出版社

WILEY
DOI: 10.1002/gepi.20283

关键词

genetic heterogeneity; meiotic map; physical map; multipoint; SNP; data reduction

资金

  1. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [P01HL030086, R01HL070751] Funding Source: NIH RePORTER
  2. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM046255, R37GM046255] Funding Source: NIH RePORTER
  3. NATIONAL INSTITUTE OF MENTAL HEALTH [K08MH074057] Funding Source: NIH RePORTER
  4. NATIONAL INSTITUTE ON AGING [R37AG011762, R01AG011762, P50AG005136] Funding Source: NIH RePORTER
  5. NHLBI NIH HHS [HL 30086, HL 070751] Funding Source: Medline
  6. NIA NIH HHS [P50 AG005136, AG 2544, AG 11762, AG 05136] Funding Source: Medline
  7. NICHD NIH HHS [HD 35465] Funding Source: Medline
  8. NIGMS NIH HHS [GM 28715, GM 46255] Funding Source: Medline
  9. NIMH NIH HHS [K08 MH074057] Funding Source: Medline

向作者/读者索取更多资源

Group 9 participants carried out linkage analysis of the Centre d'Etude de Polymorphism Humain (CEPH) expression data, using strategies that ranged from focused investigation of a small number of traits to full genome scans of all available traits. Results from five key areas encompass the most important results within and across the 17 participating groups. First, both extensive genetic heterogeneity and poor predictability of mapping results based on heritability have key implications for study design. Second, choice of the map used for linkage analysis is influential, with the implication that meiotic maps are preferable to physical maps. Third, performance of different analytic methods was in general fairly consistent, with the exception of one variance-component method that uses marker allele sharing as the dependent rather than independent variable. Fourth, multivariate analysis approaches did not generally appear to provide advantages over univariate approaches for linkage detection. Finally, there were computational and analytic challenges in working with a large public data set, along with need for more data documentation.

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