Segregation Analysis Using the Unified Model

Part of the Methods in Molecular Biology book series (MIMB, volume 1666)


Segregation analysis is a basic tool in human genetics. It is a statistical method to determine if a trait, continuous or binary, has a transmission pattern in pedigrees that is consistent with Mendelian segregation. Major locus segregation is combined together with multifactorial/polygenic inheritance in the unified model. Segregation analysis as a procedure to identify the presence of segregation at a major Mendelian locus, with/without multifactorial inheritance, is introduced in this chapter. It is illustrated with the program SEGREG in the Statistical Analysis for Genetic Epidemiology (S.A.G.E.) package, which can use either regressive models or the finite polygenic mixed model to incorporate the multifactorial/polygenic component.

Key words

Segregation analysis Unified model Multifactorial inheritance Polygenic variance Familial correlation Multivariate mixed model S.A.G.E. Mendelian transmission Susceptibility Phenotypic distribution Binary trait Quantitative trait 


  1. 1.
    Elston RC, Stewart J (1971) A general model for the genetic analysis of pedigree data. Hum Hered 21:523–542CrossRefPubMedGoogle Scholar
  2. 2.
    Go RC, Elston RC, Kaplan EB (1978) Efficiency and robustness of pedigree segregation analysis. Am J Hum Genet 30:28–37PubMedPubMedCentralGoogle Scholar
  3. 3.
    Morton NE, Maclean CJ (1974) Analysis of family resemblance. III. Complex segregation analysis of quantitative traits. Am J Hum Genet 26:489–503PubMedPubMedCentralGoogle Scholar
  4. 4.
    Lalouel JM et al (1983) A unified model for complex segregation analysis. Am J Hum Genet 35:816–826PubMedPubMedCentralGoogle Scholar
  5. 5.
    S.A.G.E. 6.4: statistical analysis for genetic epidemiology; 2016.
  6. 6.
    Guo X et al (1999) Evidence of a major gene effect for angiotensinogen among Nigerians. Ann Hum Genet 63:293–300CrossRefPubMedGoogle Scholar
  7. 7.
    Sun X et al (2010) A segregation analysis of Barrett's esophagus and associated adenocarcinomas. Cancer Epidemiol Biomark Prev 19:666–674CrossRefGoogle Scholar
  8. 8.
    Bonney GE (1984) On the statistical determination of major gene mechanisms in continuous human traits: regressive models. Am J Med Genet 18:731–749CrossRefPubMedGoogle Scholar
  9. 9.
    Karunaratne PM, Elston RC (1998) A multivariate logistic model (MLM) for analyzing binary family data. Am J Med Genet 76:428–437CrossRefPubMedGoogle Scholar
  10. 10.
    Fernando RL, Stricker C, Elston RC (1994) The finite polygenic mixed model: an alternative formulation for the mixed model of inheritance. Theor Appl Genet 88:573–580CrossRefPubMedGoogle Scholar
  11. 11.
    Lange K (1997) An approximate model of polygenic inheritance. Genetics 147:1423–1430PubMedPubMedCentralGoogle Scholar
  12. 12.
    Demenais FM, Elston RC (1981) A general transmission probability model for pedigree data. Hum Hered 31:93–99CrossRefPubMedGoogle Scholar
  13. 13.
    Elston RC et al (1975) Study of the genetic transmission of hypocholesterolemia and hypertriglyceridemia in a 195 member kindred. Ann Hum Genet 39:67–87CrossRefPubMedGoogle Scholar
  14. 14.
    Self S, Liang K (1987) Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard conditions. J Am Statist Assoc 82:605–610CrossRefGoogle Scholar
  15. 15.
    Akaike H (1974) A new look at the statistical model identification. IEEE Trans Automat Contr AC 19:716–723CrossRefGoogle Scholar
  16. 16.
    Cubells JF, Sun X, Li W, Elston RC, Bonsall RW, McGrath JA, Avramopoulos D, Tang Y-L, Mercer K, Pulver AE (2011) Linkage analysis of plasma dopamine ?-hydroxylase activity in families of patients with schizophrenia. Hum Genet 130:635–643CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Box GEP, Cox DR (1964) An analysis of transformations. J Roy Stat Soc B 26:211–252Google Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Department of Population and Quantitative Health SciencesCase Western Reserve University School of MedicineClevelandUSA

Personalised recommendations