City Research Online

Abstract

This paper presents a coherent probabilistic framework for taking account of allelic dropout, stutter bands and silent alleles when interpreting STR DNA profiles from a mixture sample using peak size information arising from a PCR analysis. This information can be exploited for evaluating the evidential strength for a hypothesis that DNA from a particular person is present in the mixture. It extends an earlier Bayesian network approach that ignored such artifacts. We illustrate the use of the extended network on a published casework example.

Publication Type:	Monograph (Working Paper)
Publisher Keywords:	Allelic dropout, artifacts, Bayesian networks, DNA mixtures, peak area, probabilistic expert systems, silent alleles, STR marker, stutter bands
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School > Actuarial Science & Insurance > Statistical Research Reports

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