Old lessons learned anew: family-based methods for detecting genes responsible for quantitative and qualitative traits in the Genetic Analysis Workshop 17 mini-exome sequence data

BMC Proceedings

Proceedings

Cristina M Justice¹  Heejong Sung¹  Mera Krishnan¹  Dana Behneman¹  Alexander F Wilson¹  Jerry Cai¹  Deyana Lewis²  Claire L Simpson²  Joan E Bailey-Wilson²  Robert Wojciechowski²  Tiffany Green² 

[1] Genometrics Section, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, 31 Center Drive, 333 Cassell Drive Suite 1200, 21224, Baltimore, MD, USA;Statistical Genetics Section, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, 31 Center Drive, 333 Cassell Drive Suite 1200, 21224, Baltimore, MD, USA;

关键词: Linkage Analysis;    Minor Allele Frequency;    Causal Variant;    Qualitative Trait;    Genetic Analysis Workshop;   

DOI  :  10.1186/1753-6561-5-S9-S83

来源: Springer

【 摘 要 】

Family-based study designs are again becoming popular as new next-generation sequencing technologies make whole-exome and whole-genome sequencing projects economically and temporally feasible. Here we evaluate the statistical properties of linkage analyses and family-based tests of association for the Genetic Analysis Workshop 17 mini-exome sequence data. Based on our results, the linkage methods using relative pairs or nuclear families had low power, with the best results coming from variance components linkage analysis in nuclear families and Elston-Stewart model-based linkage analysis in extended pedigrees. For family-based tests of association, both ASSOC and ROMP performed well for genes with large effects, but ROMP had the advantage of not requiring parental genotypes in the analysis. For the linkage analyses we conclude that genome-wide significance levels appear to control type I error well but that “suggestive” significance levels do not. Methods that make use of the extended pedigrees are well powered to detect major loci segregating in the families even when there is substantial genetic heterogeneity and the trait is mainly polygenic. However, large numbers of such pedigrees will be necessary to detect all major loci. The family-based tests of association found the same major loci as the linkage analyses and detected low-frequency loci with moderate effect sizes, but control of type I error was not as stringent.

【 授权许可】

Unknown   
© Simpson et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.