Literature DB >> 12214309

On a general class of conditional tests for family-based association studies in genetics: the asymptotic distribution, the conditional power, and optimality considerations.

Christoph Lange1, Nan M Laird.   

Abstract

Family-based association tests (FBATs) provide simple and powerful tests to detect association between a genetic marker and a disease-susceptibility locus, manifest in subjects by a phenotype or disease trait. Here we propose a new class of conditional tests for family-based association studies that includes most of the established tests and their generalizations. The class of tests is very general; it can be applied to longitudinal and multivariate traits or phenotypes, multiple genetic markers, and many other situations not yet discussed in the literature. For any test in this class, we derive the asymptotic distribution under the null hypothesis, the conditional power under any alternative hypothesis, and the optimal offset for single degree of freedom tests. The proposed methodology is illustrated with a genetic study of asthma. Copyright 2002 Wiley-Liss, Inc.

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Year:  2002        PMID: 12214309     DOI: 10.1002/gepi.209

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


  51 in total

1.  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

2.  Power calculations for a general class of family-based association tests: dichotomous traits.

Authors:  Christoph Lange; Nan M Laird
Journal:  Am J Hum Genet       Date:  2002-08-12       Impact factor: 11.025

3.  IL10 gene polymorphisms are associated with asthma phenotypes in children.

Authors:  Helen Lyon; Christoph Lange; Stephen Lake; Edwin K Silverman; Adrienne G Randolph; David Kwiatkowski; Benjamin A Raby; Ross Lazarus; Katy M Weiland; Nan Laird; Scott T Weiss
Journal:  Genet Epidemiol       Date:  2004-02       Impact factor: 2.135

4.  PBAT: tools for family-based association studies.

Authors:  Christoph Lange; Dawn DeMeo; Edwin K Silverman; Scott T Weiss; Nan M Laird
Journal:  Am J Hum Genet       Date:  2004-02       Impact factor: 11.025

5.  Using the noninformative families in family-based association tests: a powerful new testing strategy.

Authors:  Christoph Lange; Dawn DeMeo; Edwin K Silverman; Scott T Weiss; Nan M Laird
Journal:  Am J Hum Genet       Date:  2003-09-18       Impact factor: 11.025

6.  On the meta-analysis of genome-wide association studies: a robust and efficient approach to combine population and family-based studies.

Authors:  Sungho Won; Qing Lu; Lars Bertram; Rudolph E Tanzi; Christoph Lange
Journal:  Hum Hered       Date:  2012-01-18       Impact factor: 0.444

Review 7.  Statistical challenges for genome-wide association studies of suicidality using family data.

Authors:  J Lasky-Su; C Lange
Journal:  Eur Psychiatry       Date:  2010-05-05       Impact factor: 5.361

8.  On genome-wide association studies for family-based designs: an integrative analysis approach combining ascertained family samples with unselected controls.

Authors:  Jessica Lasky-Su; Sungho Won; Eric Mick; Richard J L Anney; Barbara Franke; Benjamin Neale; Joseph Biederman; Susan L Smalley; Sandra K Loo; Alexandre Todorov; Stephen V Faraone; Scott T Weiss; Christoph Lange
Journal:  Am J Hum Genet       Date:  2010-03-25       Impact factor: 11.025

9.  Using ancestry matching to combine family-based and unrelated samples for genome-wide association studies.

Authors:  Andrew Crossett; Brian P Kent; Lambertus Klei; Steven Ringquist; Massimo Trucco; Kathryn Roeder; Bernie Devlin
Journal:  Stat Med       Date:  2010-12-10       Impact factor: 2.373

10.  Association of ADHD and the Protogenin gene in the chromosome 15q21.3 reading disabilities linkage region.

Authors:  K G Wigg; Y Feng; J Crosbie; R Tannock; J L Kennedy; A Ickowicz; M Malone; R Schachar; C L Barr
Journal:  Genes Brain Behav       Date:  2008-11       Impact factor: 3.449

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