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Sample size calculations for classical association and TDT-type methods using family data.

D A Tregouet1, C Pallaud, C Sass

  • 1INSERM Unite 525, Paris, France. tregouet@idf.inserm.fr

Annals of Human Genetics
|June 28, 2001
PubMed
Summary

Transmission Disequilibrium Test (TDT) methods assess genetic linkage for marker-phenotype associations. This study determines the minimum sample size for TDT and association analyses, finding TDT can require more sibs despite potential efficiency gains.

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Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Transmission Disequilibrium Test (TDT)-based methods are used to distinguish genetic linkage from population stratification in marker-phenotype associations.
  • Classical association studies are often performed first to detect marker-phenotype associations before employing TDT methods.

Purpose of the Study:

  • To propose an estimating equation (EE) procedure for analytically computing the minimum sample size required for sibship data.
  • To determine the sample size needed for detecting marker-quantitative phenotype associations and confirming them using two TDT methods.

Main Methods:

  • Utilizing an estimating equation (EE) procedure for analytical sample size calculations.
  • Comparing sample size requirements for TDT-type methods versus classical association studies in sibship data.

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Main Results:

  • The number of informative sibs needed for TDT methods can be lower than for association analyses when marker allele frequencies are extreme or familial clustering is strong.
  • However, the total number of sibs to be sampled is consistently larger for TDT methods compared to association studies to obtain sufficient informative sibs.
  • Sample size requirements can be critical in phenotype-first strategies, especially for costly phenotypes.

Conclusions:

  • The study provides analytical methods for sample size estimation in genetic association and linkage studies using TDT.
  • While TDT can be efficient with informative sibs, overall sampling needs are higher than for standard association studies.
  • Careful consideration of sample size is crucial for efficient study design, particularly in resource-intensive research settings.