Literature DB >> 9519565

Selected methodological issues in meiotic mapping of obesity genes in humans: issues of power and efficiency.

D B Allison1, N J Schork.   

Abstract

This paper focuses on methods for mapping novel obesity genes in humans via meiotic mapping techniques. By novel we mean genes that are as yet unidentified as playing a role in obesity. We begin by presenting a discussion of why we believe it is important to seek out novel obesity genes and, in particular, novel genes of small effect. In light of the arguably Herculean task of finding genes of small effect with conventional gene mapping methods, we discuss alternative methods and procedures that may enhance our ability to map novel obesity genes of small effect. Many of these methods have been discussed previously in the literature and are summarized here. These include reconceptualizing power in the context of genomewide scans, multivariate linkage approaches, the use of phenotypically extreme subjects, and the use of large sibships. These are discussed in the context of linkage studies. Association studies and disequilibrium mapping are also discussed, and again, issues involving the use of extreme phenotypes and multiple testing are included. We also provide a brief discussion of DNA pooling and transmission disequilibrium tests for quantitative traits. Finally, we advocate data pooling techniques (e.g., meta-analysis) to enhance the power and efficiency of the entire field of the genetics of obesity.

Entities:  

Mesh:

Substances:

Year:  1997        PMID: 9519565     DOI: 10.1023/a:1025696232582

Source DB:  PubMed          Journal:  Behav Genet        ISSN: 0001-8244            Impact factor:   2.805


  7 in total

1.  Complexity and power in case-control association studies.

Authors:  J A Longmate
Journal:  Am J Hum Genet       Date:  2001-04-04       Impact factor: 11.025

2.  Testing the robustness of the likelihood-ratio test in a variance-component quantitative-trait loci-mapping procedure.

Authors:  D B Allison; M C Neale; R Zannolli; N J Schork; C I Amos; J Blangero
Journal:  Am J Hum Genet       Date:  1999-08       Impact factor: 11.025

3.  Testing the robustness of the new Haseman-Elston quantitative-trait loci-mapping procedure.

Authors:  D B Allison; J R Fernández; M Heo; T M Beasley
Journal:  Am J Hum Genet       Date:  2000-05-11       Impact factor: 11.025

4.  Sibling-based tests of linkage and association for quantitative traits.

Authors:  D B Allison; M Heo; N Kaplan; E R Martin
Journal:  Am J Hum Genet       Date:  1999-06       Impact factor: 11.025

Review 5.  New approaches to investigating heterogeneity in complex traits.

Authors:  R Bomprezzi; P E Kovanen; R Martin
Journal:  J Med Genet       Date:  2003-08       Impact factor: 6.318

Review 6.  Prioritizing GWAS results: A review of statistical methods and recommendations for their application.

Authors:  Rita M Cantor; Kenneth Lange; Janet S Sinsheimer
Journal:  Am J Hum Genet       Date:  2010-01       Impact factor: 11.025

7.  Incorporation of genetic model parameters for cost-effective designs of genetic association studies using DNA pooling.

Authors:  Fei Ji; Stephen J Finch; Chad Haynes; Nancy R Mendell; Derek Gordon
Journal:  BMC Genomics       Date:  2007-07-16       Impact factor: 3.969

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.