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Title
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Room
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Genetic Analysis of Correlated Binary Data from Families
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M-Sydney
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Date / Time
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Sponsor
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Type
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08/05/2001
2:00 PM
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3:50 PM
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Biometrics Section*, ENAR
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Invited
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Organizer:
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Ramesh Ramakrishnan, Virginia Commonwealth University
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Chair:
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Tammy Massie, Virginia Commonwealth University
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Discussant:
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Floor Discussion
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3:45 PM
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Description
Analysis of family data to determine effects of genes, environment and gene by environment interaction has been a topic of growing interest among quantitative geneticists. Often the phenotypes (outcomes) of interest in these data are binary (ordinal) and are correlated. For example, the outcome may be the presence or absence of a type of cancer among family members. One of the main differences between the classical analyses of correlated binary data and the genetic analyses of family data is that in the genetic analyses, modeling the correlations among family members is the main focus, while in the classical analyses correlation is treated as a nuisance parameter. In the literature many methods have been proposed to analyze correlated binary data to test genetic hypotheses and to perform linkage analyses. This session will bring together some of the recent developments in the area. The session's speakers will include prominent researchers in this area. As the field of genomics advances rapidly in the information age the estimation of the interactions between genes and environments has become crucial. Therefore, development of genetic methodologies that facilitate inferences regarding the Gene x Environment interaction using binary (ordinal) data is of utmost importance.
The session will focus on a method for fitting genetic models using logistic regression, a method on linkage analysis and one on generating correlated binary data to perform simulations.
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