Assessing genuine parents-offspring trios for genetic association studies

Hum Hered. 2009;67(1):26-37. doi: 10.1159/000164396. Epub 2008 Oct 17.

Abstract

Objectives: Family-based association tests such as the transmission disequilibrium test (TDT) are dependent on the successful ascertainment of true nuclear family trios. Relationship misspecification inevitably occurs in a proportion of trios collected for genotyping which undetected can lead to a loss of power and increased Type I error due to biases in over-transmission of common alleles. Here, we introduce a method for evaluating the authenticity of nuclear family trios.

Methods: Operating in a Bayesian framework, our approach assesses the extent of pedigree inconsistent genotype configurations in the presence of genotyping errors. Unlike other approaches, our method: (i) utilizes information from three individuals collectively (the whole trio) rather than consider two independent pairwise relationships; (ii) down-weighs SNPs with poor performance; (iii) does not require the user to pre-define a rate of genotyping error, which is often unknown to the user and seldom fixed across the different SNPs considered which available methods unrealistically assumed.

Results: Simulation studies and comparisons with a real set of data showed that our approach is more likely to correctly identify the presence of true and misspecified trios compared to available software, accurately infers the extent of relationship misspecification in a trio and accurately estimates the genotyping error rates.

Conclusions: Assessing relationship misspecification depends on the fidelity of the genotype data used. Available algorithms are not optimised for genotyping technology with varying rates of errors across the markers. Through our comparison studies, our approach is shown to outperform available methods for assessing relationship misspecifications.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chromosome Mapping* / statistics & numerical data
  • Computer Simulation
  • Epidemiologic Studies*
  • Female
  • Genotype
  • Humans
  • Male
  • Models, Genetic*
  • Parents*
  • Pedigree
  • Polymorphism, Single Nucleotide