Literature DB >> 10782012

A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information.

D Rabinowitz1, N Laird.   

Abstract

A general approach to family-based examinations of association between marker alleles and traits is proposed. The approach is based on computing p values by comparing test statistics for association to their conditional distributions given the minimal sufficient statistic under the null hypothesis for the genetic model, sampling plan and population admixture. The approach can be applied with any test statistic, so any kind of phenotype and multi-allelic markers may be examined, and covariates may be included in analyses. By virtue of the conditioning, the approach results in correct type I error probabilities regardless of population admixture, the true genetic model and the sampling strategy. An algorithm for computing the conditional distributions is described, and the results of the algorithm for configurations of nuclear families are presented. The algorithm is applicable with all pedigree structures and all patterns of missing marker allele information. Copyright 2000 S. Karger AG, Basel

Mesh:

Substances:

Year:  2000        PMID: 10782012     DOI: 10.1159/000022918

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  286 in total

1.  Correcting for a potential bias in the pedigree disequilibrium test.

Authors:  E R Martin; M P Bass; N L Kaplan
Journal:  Am J Hum Genet       Date:  2001-04       Impact factor: 11.025

2.  Transmission/disequilibrium test meets measured haplotype analysis: family-based association analysis guided by evolution of haplotypes.

Authors:  H Seltman; K Roeder; B Devlin
Journal:  Am J Hum Genet       Date:  2001-04-10       Impact factor: 11.025

3.  The transmission/disequilibrium test and parental-genotype reconstruction for X-chromosomal markers.

Authors:  S Horvath; N M Laird; M Knapp
Journal:  Am J Hum Genet       Date:  2000-03       Impact factor: 11.025

4.  Family-based tests of association and linkage that use unaffected sibs, covariates, and interactions.

Authors:  K L Lunetta; S V Faraone; J Biederman; N M Laird
Journal:  Am J Hum Genet       Date:  2000-02       Impact factor: 11.025

5.  Informative missingness in genetic association studies: case-parent designs.

Authors:  Andrew S Allen; Paul J Rathouz; Glen A Satten
Journal:  Am J Hum Genet       Date:  2003-02-14       Impact factor: 11.025

6.  Power and design considerations for a general class of family-based association tests: quantitative traits.

Authors:  Christoph Lange; Dawn L DeMeo; Nan M Laird
Journal:  Am J Hum Genet       Date:  2002-11-21       Impact factor: 11.025

7.  Test of association between 10 single nucleotide polymorphisms in the oxytocin receptor gene and conduct disorder.

Authors:  Joseph T Sakai; Thomas J Crowley; Michael C Stallings; Matthew McQueen; John K Hewitt; Christian Hopfer; Nicole R Hoft; Marissa A Ehringer
Journal:  Psychiatr Genet       Date:  2012-04       Impact factor: 2.458

8.  A comparison of popular TDT-generalizations for family-based association analysis.

Authors:  Julian Hecker; Nan Laird; Christoph Lange
Journal:  Genet Epidemiol       Date:  2019-01-04       Impact factor: 2.135

9.  Genetic association test for multiple traits at gene level.

Authors:  Xiaobo Guo; Zhifa Liu; Xueqin Wang; Heping Zhang
Journal:  Genet Epidemiol       Date:  2012-10-02       Impact factor: 2.135

10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.