Sensitivity of inferences in forensic genetics to assumptions about founding genes
Peter J. Green and Julia Mortera
Source: Ann. Appl. Stat. Volume 3, Number 2 (2009), 731-763.
Abstract
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.
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
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Links and Identifiers
Permanent link to this document: http://projecteuclid.org/euclid.aoas/1245676193
Digital Object Identifier: doi:10.1214/09-AOAS235
Zentralblatt MATH identifier:
1166.62083
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