Combining family- and population-based imputation data for association analysis of rare and common variants in large pedigrees

Mohamad Saad, Ellen M. Wijsman

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

In the last two decades, complex traits have become the main focus of genetic studies. The hypothesis that both rare and common variants are associated with complex traits is increasingly being discussed. Family-based association studies using relatively large pedigrees are suitable for both rare and common variant identification. Because of the high cost of sequencing technologies, imputation methods are important for increasing the amount of information at low cost. A recent family-based imputation method, Genotype Imputation Given Inheritance (GIGI), is able to handle large pedigrees and accurately impute rare variants, but does less well for common variants where population-based methods perform better. Here, we propose a flexible approach to combine imputation data from both family- and population-based methods. We also extend the Sequence Kernel Association Test for Rare and Common variants (SKAT-RC), originally proposed for data from unrelated subjects, to family data in order to make use of such imputed data. We call this extension "famSKAT-RC." We compare the performance of famSKAT-RC and several other existing burden and kernel association tests. In simulated pedigree sequence data, our results show an increase of imputation accuracy from use of our combining approach. Also, they show an increase of power of the association tests with this approach over the use of either family- or population-based imputation methods alone, in the context of rare and common variants. Moreover, our results show better performance of famSKAT-RC compared to the other considered tests, in most scenarios investigated here.

Original languageEnglish
Pages (from-to)579-590
Number of pages12
JournalGenetic Epidemiology
Volume38
Issue number7
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

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Pedigree
Population
High-Cost Technology
Genotype
Costs and Cost Analysis

Keywords

  • Association analysis
  • Burden test
  • Inheritance vectors
  • Kernel statistic
  • MCMC
  • Mixed linear model
  • Sequence data
  • Variance components

ASJC Scopus subject areas

  • Epidemiology
  • Genetics(clinical)

Cite this

Combining family- and population-based imputation data for association analysis of rare and common variants in large pedigrees. / Saad, Mohamad; Wijsman, Ellen M.

In: Genetic Epidemiology, Vol. 38, No. 7, 01.01.2014, p. 579-590.

Research output: Contribution to journalArticle

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