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