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June 2009 Sensitivity of inferences in forensic genetics to assumptions about founding genes
Peter J. Green, Julia Mortera
Ann. Appl. Stat. 3(2): 731-763 (June 2009). DOI: 10.1214/09-AOAS235


Many forensic genetics problems can be handled using structured systems of discrete variables, for which Bayesian networks offer an appealing practical modeling framework, and allow inferences to be computed by probability propagation methods. However, when standard assumptions are violated—for example, when allele frequencies are unknown, there is identity by descent or the population is heterogeneous—dependence is generated among founding genes, that makes exact calculation of conditional probabilities by propagation methods less straightforward. Here we illustrate different methodologies for assessing sensitivity to assumptions about founders in forensic genetics problems. These include constrained steepest descent, linear fractional programming and representing dependence by structure. We illustrate these methods on several forensic genetics examples involving criminal identification, simple and complex disputed paternity and DNA mixtures.


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Peter J. Green. Julia Mortera. "Sensitivity of inferences in forensic genetics to assumptions about founding genes." Ann. Appl. Stat. 3 (2) 731 - 763, June 2009.


Published: June 2009
First available in Project Euclid: 22 June 2009

zbMATH: 1166.62083
MathSciNet: MR2750680
Digital Object Identifier: 10.1214/09-AOAS235

Keywords: Bayesian networks , coancestry coefficient , constrained steepest descent , criminal identification , disputed paternity , DNA mixtures , heterogeneous population , identity by descent , inbreeding , kinship , linear fractional programming , Pólya urn , uncertainty in allele frequencies

Rights: Copyright © 2009 Institute of Mathematical Statistics


Vol.3 • No. 2 • June 2009
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