title: A clustering algorithm using DNA marker information for sub-pedigree reconstruction.
abstract: In a mass disaster scenario in which many people are dead, it may be that small family groups are among the dead, and investigators may need to identify such groups, e.g., to return bodies to living relatives for burial. We consider the problem of identifying small groups of closely related people within a large group of people through the use of DNA marker information. We propose a likelihood-ratio-based distance measure of the relatedness between pairs of individuals and use an estimate of this measure as a means of clustering related people into groups. We show the effectiveness of our approach on real examples and through simulations, which suggest that the method is quite reliable for identifying very close relationships. We discuss the use of our clustering algorithm in a two-stage pedigree reconstruction procedure and suggest directions in which the analysis could be extended. Applications include the identification of family groups among bodies found in mass graves and identification of family groups in animal populations.
authors.affiliation: Faculty of Actuarial Science and Statistics, Cass Business School, City of London, UK. rgc@city.ac.uk
authors.forename: Robert G
authors.initials: RG
authors.lastname: Cowell
authors.forename: Petter
authors.initials: P
authors.lastname: Mostad
mesh_terms: D000465:Algorithms; D002648:Child; D016000:Cluster Analysis; D016172:DNA Fingerprinting / Q000379:methods*; D005260:Female; D005819:Genetic Markers; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D010375:Pedigree; D020080:Tandem Repeat Sequences
chemical_list: D005819:Genetic Markers