Literature DB >> 11865718

The power of the transmission disequilibrium test (TDT) with both case-parent and control-parent trios.

H W Deng1, W M Chen.   

Abstract

The transmission disequilibrium test (TDT) customarily uses affected children and their parents (often case-parent trios, TDTD). Control-parent trios are necessary to guard against spurious significant results due to segregation distortion but are not generally utilized in the identification of disease susceptibility loci (DSL). Controls are often easy to recruit and the TDT can easily be extended to include control-parent trios into the analyses with unrelated case-parent trios. We present an extension of the TDT (TDTDC) that incorporates unrelated cases and controls and their parents into a single analysis. We develop a simple and accurate analytical method for computing the statistical power of various TDT (e.g. the TDTD, TDTDC, TDTDC and TDTC that employ control-parent trios only) under any genetic model. We investigated the power of these TDT, and particularly compared the relative power of the TDTD and TDTDC. We found that the TDTDC is almost always more powerful than the TDTC and TDTD. The relative power of the TDTDC and TDTD depends largely upon a number of parameters identified in the study. This study provides a basis for efficient use of control-parent trios in DSL identification.

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Year:  2001        PMID: 11865718     DOI: 10.1017/s001667230100533x

Source DB:  PubMed          Journal:  Genet Res        ISSN: 0016-6723            Impact factor:   1.588


  11 in total

1.  Power for genetic association studies with random allele frequencies and genotype distributions.

Authors:  Walter T Ambrosius; Ethan M Lange; Carl D Langefeld
Journal:  Am J Hum Genet       Date:  2004-03-12       Impact factor: 11.025

2.  An extension of the transmission disequilibrium test incorporating imprinting.

Authors:  Yue-Qing Hu; Ji-Yuan Zhou; Wing K Fung
Journal:  Genetics       Date:  2006-12-28       Impact factor: 4.562

3.  Genetics of Kidneys in Diabetes (GoKinD) study: a genetics collection available for identifying genetic susceptibility factors for diabetic nephropathy in type 1 diabetes.

Authors:  Patricia W Mueller; John J Rogus; Patricia A Cleary; Yuan Zhao; Adam M Smiles; Michael W Steffes; Jean Bucksa; Therese B Gibson; Suzanne K Cordovado; Andrzej S Krolewski; Concepcion R Nierras; James H Warram
Journal:  J Am Soc Nephrol       Date:  2006-06-14       Impact factor: 10.121

4.  X-chromosome genetic association test incorporating X-chromosome inactivation and imprinting effects.

Authors:  Wei Liu; Bei-Qi Wang; Guojun Liu-Fu; Wing Kam Fung; Ji-Yuan Zhou
Journal:  J Genet       Date:  2019-11       Impact factor: 1.166

5.  PolyGEE: a generalized estimating equation approach to the efficient and robust estimation of polygenic effects in large-scale association studies.

Authors:  Julian Hecker; Dmitry Prokopenko; Christoph Lange; Heide Loehlein Fier
Journal:  Biostatistics       Date:  2018-07-01       Impact factor: 5.899

Review 6.  Gene-environment interaction tests for family studies with quantitative phenotypes: A review and extension to longitudinal measures.

Authors:  Hortensia Moreno-Macias; Isabelle Romieu; Stephanie J London; Nan M Laird
Journal:  Hum Genomics       Date:  2010-06       Impact factor: 4.639

7.  Sample size computation for association studies using case-parents design.

Authors:  Najla Kharrat; Imen Ayadi; Ahmed Rebaï
Journal:  J Genet       Date:  2006-12       Impact factor: 1.508

8.  Learning about the X from our parents.

Authors:  Alison S Wise; Min Shi; Clarice R Weinberg
Journal:  Front Genet       Date:  2015-02-10       Impact factor: 4.599

9.  Analysis of Case-Parent Trios Using a Loglinear Model with Adjustment for Transmission Ratio Distortion.

Authors:  Lam O Huang; Claire Infante-Rivard; Aurélie Labbe
Journal:  Front Genet       Date:  2016-08-31       Impact factor: 4.599

10.  A robust test for X-chromosome genetic association accounting for X-chromosome inactivation and imprinting.

Authors:  Yu Zhang; Si-Qi Xu; Wei Liu; Wing Kam Fung; Ji-Yuan Zhou
Journal:  Genet Res (Camb)       Date:  2020-04-01       Impact factor: 1.588

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