Literature DB >> 17123304

Informative-transmission disequilibrium test (i-TDT): combined linkage and association mapping that includes unaffected offspring as well as affected offspring.

Chao-Yu Guo1, Kathryn L Lunetta, Anita L DeStefano, Jose M Ordovas, L Adrienne Cupples.   

Abstract

To date, there is no test valid for the composite null hypothesis of no linkage or no association that utilizes transmission information from heterozygous parents to their unaffected offspring as well as the affected offspring from ascertained nuclear families. Since the unaffected siblings also provide information about linkage and association, we introduce a new strategy called the informative-transmission disequilibrium test (i-TDT), which uses transmission information from heterozygous parents to all of the affected and unaffected offspring in ascertained nuclear families and provides a valid chi-square test for both linkage and association. The i-TDT can be used in various study designs and can accommodate all types of independent nuclear families with at least one affected offspring. We show that the transmission/disequilibrium test (TDT) (Spielman et al. [1993] Am. J. Hum. Genet. 52:506-516) is a special case of the i-TDT, if the study sample contains only case-parent trios. If the sample contains only affected and unaffected offspring without parental genotypes, the i-TDT is equivalent to the sibship disequilibrium test (SDT) (Horvath and Laird [1998] Am. J. Hum. Genet. 63:1886-1897. In addition, the test statistic of i-TDT is simple, explicit and can be implemented easily without intensive computing. Through computer simulations, we demonstrate that power of the i-TDT can be higher in many circumstances compared to a method that uses affected offspring only. Applying the i-TDT to the Framingham Heart Study data, we found that the apolipoprotein E (APOE) gene is significantly linked and associated with cross-sectional measures and longitudinal changes in total cholesterol.

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Year:  2007        PMID: 17123304     DOI: 10.1002/gepi.20195

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


  3 in total

1.  Pseudosibship methods in the case-parents design.

Authors:  Zhaoxia Yu; Li Deng
Journal:  Stat Med       Date:  2011-09-23       Impact factor: 2.373

Review 2.  Review and evaluation of methods correcting for population stratification with a focus on underlying statistical principles.

Authors:  Hemant K Tiwari; Jill Barnholtz-Sloan; Nathan Wineinger; Miguel A Padilla; Laura K Vaughan; David B Allison
Journal:  Hum Hered       Date:  2008-03-31       Impact factor: 0.444

3.  Transmission/disequilibrium tests incorporating unaffected offspring.

Authors:  Qinyu Wei; Yuanli Chen; Zheng Zeng; Chang Shu; Lu Long; Jianhua Lu; Yangxin Huang; Ping Yin
Journal:  PLoS One       Date:  2014-12-23       Impact factor: 3.240

  3 in total

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