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Title: Structured incorporation of prior information in relationship identification problems
Authors: Sheehan, Nuala A.
Egeland, Thore
First Published: 18-Jan-2007
Publisher: Blackwell
Citation: Annals of Human Genetics, 2007, 71 (4), pp. 501-508
Abstract: The objective of this paper is to show how various sources of information can be modelled and integrated to address relationship identification problems. Applications come from areas as diverse as evolution and conservation research, genealogical research in human, plant and animal populations, and forensic problems including paternity cases, identification following disasters, family reunion and immigration issues. We propose assigning a prior probability distribution to the sample space of pedigrees, calculating the likelihood based on DNA data using available software and posterior probabilities using Bayes' Theorem. Our emphasis here is on the modelling of this prior information in a formal and consistent manner. We introduce the distinction between local and global prior information whereby local information usually applies to particular components of the pedigree and global prior information refers to more general features. When it is difficult to decide on a prior distribution, robustness to various choices should be studied. When suitable prior information is not available, a flat prior can be used which will then correspond to a strict likelihood approach. In practice, prior information is often considered for these problems, but in a generally ad hoc manner. This paper offers a consistent alternative. We emphasise that many practical problems can be addressed using freely available software.
DOI Link: 10.1111/j.1469-1809.2006.00345.x
ISSN: 0003-4800
eISSN: 1469-1809
Version: Post print
Status: Peer reviewed
Type: Article
Rights: © 2007 The Authors. Journal compilation © 2007 University College London. Deposited with reference to the publisher’s archiving policy available on the SHERPA/RoMEO website. The definitive version is available at
Appears in Collections:Published Articles, Dept. of Health Sciences
Published Articles, Dept. of Genetics

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