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

Chapter
Part of the Statistics for Biology and Health book series (SBH)

Abstract

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.

Keywords

Covariance Schizophrenia Thalassemia 

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Copyright information

© Springer Science+Business Media. LLC 2011

Authors and Affiliations

  1. 1.Department of BiostatisticsHarvard UniversityBostonUSA

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