Effects of stratification in the analysis of affected-sib-pair data: benefits and costs

Am J Hum Genet. 2000 Feb;66(2):567-75. doi: 10.1086/302748.

Abstract

The benefits and costs of stratification of affected-sib-pair (ASP) data were examined in three situations: (1) when there is no difference in identity-by-descent (IBD) allele sharing between stratified and unstratified ASP data sets; (2) when there is an increase in IBD allele sharing in one of the stratified groups; and (3) when the data are stratified on the basis of IBD allele-sharing status at one locus, and the stratified ASPs are then analyzed for linkage at a second locus. When there is no difference in IBD sharing between strata, a penalty is always paid for stratifying the data. The loss of power to detect linkage in the stratified ASP data sets is the result of multiple testing and the smaller sample size within individual strata. In the case in which etiologic heterogeneity (i.e., severity of phenotype, age at onset) represents genetic heterogeneity, the power to detect linkage can be increased by stratifying the ASP data. This benefit is obtained when there is sufficient IBD allele sharing and sample sizes. Once linkage has been established for a given locus, data can be stratified on the basis of IBD status at this locus and can be tested for linkage at a second locus. When the relative risk is in the vicinity of 1, the power to detect linkage at the second locus is always greater for the unstratified ASP data set. Even for values of the relative risk that diverge sufficiently from 1, with adequate sample sizes and IBD allele sharing, the benefits of stratifying ASP data are minimal.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Age of Onset
  • Alleles
  • Chromosome Mapping / methods*
  • Chromosome Mapping / statistics & numerical data
  • Genetic Diseases, Inborn / epidemiology
  • Genetic Diseases, Inborn / genetics*
  • Genetic Heterogeneity
  • Genetic Linkage / genetics*
  • Genetic Predisposition to Disease / genetics
  • Humans
  • Matched-Pair Analysis
  • Nuclear Family*
  • Phenotype
  • Sample Size