Literature DB >> 19924706

Combining information from linkage and association methods.

Elizabeth E Marchani1, Andrea Callegaro, E Warwick Daw, Ellen M Wijsman.   

Abstract

Group 12 evaluated approaches to incorporate outside information or otherwise optimize traditional linkage and association analyses. The abundance of available data allowed exploration of identity-by-descent (IBD) estimation, score statistics, formal combination of linkage and association testing, significance estimation, and replication. We observed that IBD estimation can be optimized with a subset of marker data while estimation of inheritance vectors can provide both IBD estimates and a measure of their uncertainty. Score statistics incorporating covariates or combining association and linkage information performed at least as well as standard approaches while requiring less computation time. The formal combination of linkage and association methods may be fruitful, although the nature of the simulated data limited our conclusions. Estimation of significance may be improved through simulation, correction for cryptic relatedness, and the inclusion of prior information. Replication using real data provided consistent results, though the same was not true of simulated data replicates. Overall, we found that increasing the amount of available data limits analyses due to computational constraints and motivates the need to improve methods for the identification of complex-trait genes. (c) 2009 Wiley-Liss, Inc.

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Year:  2009        PMID: 19924706      PMCID: PMC2910520          DOI: 10.1002/gepi.20477

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


  19 in total

1.  Mapping quantitative trait loci in oligogenic models.

Authors:  H K Tang; D Siegmund
Journal:  Biostatistics       Date:  2001-06       Impact factor: 5.899

2.  Stratified false discovery control for large-scale hypothesis testing with application to genome-wide association studies.

Authors:  Lei Sun; Radu V Craiu; Andrew D Paterson; Shelley B Bull
Journal:  Genet Epidemiol       Date:  2006-09       Impact factor: 2.135

3.  Regression-based multivariate linkage analysis with an application to blood pressure and body mass index.

Authors:  T Wang; R C Elston
Journal:  Ann Hum Genet       Date:  2007-01       Impact factor: 1.670

4.  Were genome-wide linkage studies a waste of time? Exploiting candidate regions within genome-wide association studies.

Authors:  Yun J Yoo; Shelley B Bull; Andrew D Paterson; Daryl Waggott; Lei Sun
Journal:  Genet Epidemiol       Date:  2010-02       Impact factor: 2.135

5.  Case-control association testing in the presence of unknown relationships.

Authors:  Yoonha Choi; Ellen M Wijsman; Bruce S Weir
Journal:  Genet Epidemiol       Date:  2009-12       Impact factor: 2.135

6.  Genome-wide association and linkage analysis of quantitative traits: comparison of likelihood-ratio test and conditional score statistic.

Authors:  Audrey E Hendricks; Yanyan Zhu; Josée Dupuis
Journal:  BMC Proc       Date:  2009-12-15

7.  Comparison of univariate and multivariate linkage analysis of traits related to hypertension.

Authors:  Courtney Gray-McGuire; Yeunjoo Song; Nathan J Morris; Catherine M Stein
Journal:  BMC Proc       Date:  2009-12-15

8.  Contrasting identity-by-descent estimators, association studies, and linkage analyses using the Framingham Heart Study data.

Authors:  Elizabeth E Marchani; Yanming Di; Yoonha Choi; Charles Cheung; Ming Su; Frederick Boehm; Elizabeth A Thompson; Ellen M Wijsman
Journal:  BMC Proc       Date:  2009-12-15

9.  A framework for analyzing both linkage and association: an analysis of Genetic Analysis Workshop 16 simulated data.

Authors:  E Warwick Daw; Jevon Plunkett; Mary Feitosa; Xiaoyi Gao; Andrew Van Brunt; Duanduan Ma; Jacek Czajkowski; Michael A Province; Ingrid Borecki
Journal:  BMC Proc       Date:  2009-12-15

10.  Cloning of a gene bearing missense mutations in early-onset familial Alzheimer's disease.

Authors:  R Sherrington; E I Rogaev; Y Liang; E A Rogaeva; G Levesque; M Ikeda; H Chi; C Lin; G Li; K Holman; T Tsuda; L Mar; J F Foncin; A C Bruni; M P Montesi; S Sorbi; I Rainero; L Pinessi; L Nee; I Chumakov; D Pollen; A Brookes; P Sanseau; R J Polinsky; W Wasco; H A Da Silva; J L Haines; M A Perkicak-Vance; R E Tanzi; A D Roses; P E Fraser; J M Rommens; P H St George-Hyslop
Journal:  Nature       Date:  1995-06-29       Impact factor: 49.962

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