Literature DB >> 16025442

A method for identifying genes related to a quantitative trait, incorporating multiple siblings and missing parents.

Emily O Kistner1, Clarice R Weinberg.   

Abstract

When studying either qualitative or quantitative traits, tests of association in the presence of linkage are necessary for fine-mapping. In a previous report, we suggested a polytomous logistic approach to testing linkage and association between a di-allelic marker and a quantitative trait locus, using genotyped triads, consisting of an individual whose quantitative trait has been measured and his or her two parents. Here we extend that approach to incorporate marker information from entire nuclear families. By computing a weighted score function instead of a maximum likelihood test, we allow for both an unspecified correlation structure between siblings and "informative" family size. Both this approach and our original approach allow for population admixture by conditioning on parental genotypes. The proposed method allows for missing parental genotype data through a multiple imputation procedure. We use simulations based on a population with admixture to compare our method to a popular non-parametric family-based association test (FBAT), testing the null of no association in the presence of linkage.

Entities:  

Mesh:

Year:  2005        PMID: 16025442     DOI: 10.1002/gepi.20084

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  7 in total

1.  Using cases and parents to study multiplicative gene-by-environment interaction.

Authors:  Emily O Kistner; Min Shi; Clarice R Weinberg
Journal:  Am J Epidemiol       Date:  2009-05-29       Impact factor: 4.897

2.  Within-Cluster Resampling for Analysis of Family Data: Ready for Prime-Time?

Authors:  Hemant K Tiwari; Amit Patki; David B Allison
Journal:  Stat Interface       Date:  2010-04-01       Impact factor: 0.582

3.  On combining triads and unrelated subjects data in candidate gene studies: an application to data on testicular cancer.

Authors:  Li Hsu; Jacqueline R Starr; Yingye Zheng; Stephen M Schwartz
Journal:  Hum Hered       Date:  2008-12-12       Impact factor: 0.444

4.  The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions.

Authors:  Michelle M Clark; John Blangero; Thomas D Dyer; Eric M Sobel; Janet S Sinsheimer
Journal:  Ann Hum Genet       Date:  2015-11-15       Impact factor: 1.670

5.  Dealing with missing data in family-based association studies: a multiple imputation approach.

Authors:  Pascal Croiseau; Emmanuelle Génin; Heather J Cordell
Journal:  Hum Hered       Date:  2007-03-07       Impact factor: 0.444

6.  Human Birth Weight and Reproductive Immunology: Testing for Interactions between Maternal and Offspring KIR and HLA-C Genes.

Authors:  Michelle M Clark; Olympe Chazara; Eric M Sobel; Håkon K Gjessing; Per Magnus; Ashley Moffett; Janet S Sinsheimer
Journal:  Hum Hered       Date:  2017-02-18       Impact factor: 0.444

7.  Quantitative trait association in parent offspring trios: Extension of case/pseudocontrol method and comparison of prospective and retrospective approaches.

Authors:  Eleanor Wheeler; Heather J Cordell
Journal:  Genet Epidemiol       Date:  2007-12       Impact factor: 2.135

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.