Estimating the number of contributors to forensic DNA mixtures: does maximum likelihood perform better than maximum allele count?

نویسندگان

  • Hinda Haned
  • Laurent Pène
  • Jean R Lobry
  • Anne B Dufour
  • Dominique Pontier
چکیده

Determining the number of contributors to a forensic DNA mixture using maximum allele count is a common practice in many forensic laboratories. In this paper, we compare this method to a maximum likelihood estimator, previously proposed by Egeland et al., that we extend to the cases of multiallelic loci and population subdivision. We compared both methods' efficiency for identifying mixtures of two to five individuals in the case of uncertainty about the population allele frequencies and partial profiles. The proportion of correctly resolved mixtures was >90% for both estimators for two- and three-person mixtures, while likelihood maximization yielded success rates 2- to 15-fold higher for four- and five-person mixtures. Comparable results were obtained in the cases of uncertain allele frequencies and partial profiles. Our results support the use of the maximum likelihood estimator to report the number of contributors when dealing with complex DNA mixtures.

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عنوان ژورنال:
  • Journal of forensic sciences

دوره 56 1  شماره 

صفحات  -

تاریخ انتشار 2011