Abstract
In both criminal cases and civil cases, there is an increasing demand for the analysis of DNA mixtures involving relationships. The goal might be, for example, to identify the contributors to a DNA mixture where the donors may be related, or to infer the relationship between individuals based on a mixture. This paper introduces an approach to modelling and computation for DNA mixtures involving contributors with arbitrarily complex relationships. It builds on an extension of Jacquard's condensed coefficients of identity, to specify and compute with joint relationships, not only pairwise ones, including the possibility of inbreeding. The methodology developed is applied to two casework examples involving a missing person, and simulation studies of performance, in which the ability of the methodology to recover complex relationship information from synthetic data with known ‘true’ family structure is examined. The methods used to analyse the examples are implemented in the new KinMix R package that extends the DNAmixtures package to allow for modelling DNA mixtures with related contributors.
Original language | English |
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Pages (from-to) | 1049-1082 |
Number of pages | 34 |
Journal | Journal of the Royal Statistical Society. Series C: Applied Statistics |
Volume | 70 |
Issue number | 4 |
Early online date | 7 Jul 2021 |
DOIs | |
Publication status | Published - Aug 2021 |
Bibliographical note
Funding Information:We thank Amke Caliebe, Thore Egeland and Michael Nothnagel for organising an excellent workshop on Advanced Statistical and Stochastic Methods in Forensic Genetics, in Cologne in August 2018, and acknowledge fruitful conversations with Marjan Sjerps, Nuala Sheehan, Torben Tvedebrink, and Magnus Dehli Vigeland at and after the meeting, and also helpful correspondence with Elizabeth Thompson, and comments from Phil Dawid. Oskar Hansson was very helpful in discussion about using his package pcrsim. We also thank Lourdes Prieto, Comisar?a General de Polic?a Cient?fica, DNA Laboratory, Madrid, Spain for providing the data for the real case applications. Finally, we are indebted to the referees for their careful reviews, which have led to a much improved presentation of these ideas.
Publisher Copyright:
© 2021 The Authors. Journal of the Royal Statistical Society: Series C (Applied Statistics) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society
Keywords
- Bayesian networks
- coefficients of identity
- criminal identification
- disputed paternity
- DNA mixtures
- identity by descent
- inbreeding
- kinship
- uncertainty in allele frequencies