Software for generating liability distributions for pedigrees conditional on their observed disease states and covariates

Campbell, Desmond D. and Sham, Pak C. and Knight, Jo and Wickham, Harvey and Landau, Sabine (2010) Software for generating liability distributions for pedigrees conditional on their observed disease states and covariates. Genetic Epidemiology, 34 (2). pp. 159-170. ISSN 0741-0395

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Abstract

For many multifactorial diseases, aetiology is poorly understood. A major research aim is the identification of disease predictors (environmental, biological, and genetic markers). In order to achieve this, a two-stage approach is proposed. The initial or synthesis stage combines observed pedigree data with previous genetic epidemiological research findings, to produce estimates of pedigree members' disease risk and predictions of their disease liability. A further analysis stage uses the latter as inputs to look for associations with potential disease markers. The incorporation of previous research findings into an analysis should lead to power gains. It also allows separate predictions for environmental and genetic liabilities to be generated. This should increase power for detecting disease predictors that are environmental or genetic in nature. Finally, the approach brings pragmatic benefits in terms of data reduction and synthesis, improving comprehensibility, and facilitating the use of existing statistical genetics tools. In this article we present a statistical model and Gibbs sampling approach to generate liability predictions for multifactorial disease for the synthesis stage. We have implemented the approach in a software program. We apply this program to a specimen disease pedigree, and discuss the results produced, comparing its results with those generated under a more naïve model. We also detail simulation studies that validate the software's operation.

Item Type: Journal Article
Journal or Publication Title: Genetic Epidemiology
Additional Information: 2009 Wiley-Liss, Inc.
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/2700/2713
Subjects:
ID Code: 79900
Deposited By: ep_importer_pure
Deposited On: 07 Jun 2016 15:48
Refereed?: Yes
Published?: Published
Last Modified: 01 Jan 2020 09:46
URI: https://eprints.lancs.ac.uk/id/eprint/79900

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