Aggregation, Heritability and Segregation Analysis: Modeling Genetic Inheritance Without Genetic Data

  • Nan M. Laird
  • Christoph Lange
Part of the Statistics for Biology and Health book series (SBH)


Aggregation and heritability analyses are designed to show that diseases, or phenotypes more generally, have a genetic basis by investigating patterns of phenotypic correlation between relatives; segregation analysis is used to find support for a specific genetic model underlying the inheritance patterns observed in families. They all involve modeling phenotypic data on families, or pedigrees, without using any genetic data. As such, all were developed during the time when genotyping was expensive, labor intensive, and not widely available. Today, the general concepts used in aggregation and heritability analysis are widely accepted as useful measures of the degree to which traits are inherited; most researchers would not undertake genetic analysis without evidence of aggregation or heritability of the trait. Using segregation analysis to determine the model of inheritance at the disease locus was essential in planning parametric linkage analyses, as described in Chapter 6, but the current popularity of non-parametric linkage analysis and association analysis has put segregation analysis somewhat on the sideline. Although this chapter can be skipped if the reader’s primary interest is association, our coverage of these methods is brief and the concepts are useful to anyone with an interest in statistical genetics. In particular, the approach used to construct a likelihood for pedigree data given in Section 4.1 serves as a basis for other analyses in linkage and association discussed in later chapters.


Mating Type Segregation Analysis Sickle Cell Trait Attributable Fraction Disease Allele 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Burnham K, Anderson D (2004) Understanding AIC and BIC in model selection. Sociological Methods & Research 33(2):161–304MathSciNetCrossRefGoogle Scholar
  2. Coon K, Myers A, Craig D, Webster J, Pearson J, Lince D, Zismann V, Beach T, Leung D, Bryden L, et al (2007) A high-density whole-genome association study reveals that APOE is the major susceptibility gene for sporadic late-onset Alzheimer’s disease. The Journal of Clinical Psychiatry 68(4):613CrossRefGoogle Scholar
  3. Edwards J (1963) The genetic basis of common disease. The American Journal of Medicine 34(5):627–638CrossRefGoogle Scholar
  4. Guo S (1998) Inflation of sibling recurrence-risk ratio, due to ascertainment bias and/or overreporting. American Journal of Human Genetics 63(1):252–258CrossRefGoogle Scholar
  5. Javaras K, Laird N, Hudson J, Ripley B (2010) Estimating disease prevalence using relatives of case and control probands. Biometrics 66(1):214–221, Epub 2009 May 18MathSciNetCrossRefMATHGoogle Scholar
  6. Laird N, Fitzmaurice G, Schwartz A (2000a) The analysis of case–control data: epidemiologic studies of familial aggregation. Handbook of Environmental and Public Health Statistics 18:465–482Google Scholar
  7. Neel J, Valentine W (1947) Further studies on the genetics of thalassemia. Genetics 32(1):38–63Google Scholar
  8. Risch N (1990a) Linkage strategies for genetically complex traits. I. Multilocus models. American Journal of Human Genetics 46(2):222–228MathSciNetGoogle Scholar
  9. Taliaferro W, Huck J (1923) The inheritance of sickle-cell anaemia in man. Genetics 8(6):594–598Google Scholar
  10. Thomas D (2004) Statistical Methods in Genetic Epidemiology. Wiley, New York, NYMATHGoogle Scholar
  11. Falconer D, Mackay T (1996) Heritability. Introduction to Quantitative Genetics pp 160–183. 4th edn. Benjamin Cummings.Google Scholar
  12. Newcombe H (1964) Tests for polygenic inheritance. In: Second International Conference on Congenital Malformations. International Medical Congress, New York, NY, p 348Google Scholar

Copyright information

© Springer Science+Business Media. LLC 2011

Authors and Affiliations

  1. 1.Department of BiostatisticsHarvard UniversityBostonUSA

Personalised recommendations