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Mixtures with relatives and linked markers.

Guro Dørum1, Daniel Kling2,3, Andreas Tillmar4,5

  • 1Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway. guro.dorum@nmbu.no.

International Journal of Legal Medicine
|November 29, 2015
PubMed
Summary

This study addresses complex forensic DNA mixtures with linked genetic markers and related individuals. It introduces a framework for calculating likelihood ratios, improving mixture analysis power.

Keywords:
DNA mixturesForensicsKinshipLikelihood ratioLinkageLinkage disequilibrium

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Area of Science:

  • Forensic Genetics
  • Statistical Genetics
  • Population Genetics

Background:

  • Mixture DNA profiles are common in forensic science.
  • Existing statistical methods often assume unrelated contributors and unlinked genetic markers.
  • Linkage between markers and relatedness among contributors complicate mixture analysis.

Purpose of the Study:

  • To develop a statistical framework for analyzing DNA mixtures with linked markers and related contributors.
  • To explore the impact of marker linkage on the power of forensic mixture interpretation.
  • To address limitations of current methods that assume marker independence.

Main Methods:

  • Developed a likelihood ratio framework for general relationships and linked markers.
  • Focused on pairs of linked autosomal markers and X-chromosomal markers.
  • Investigated the influence of linkage disequilibrium (allelic association) on likelihood ratios.

Main Results:

  • Linkage introduces dependencies between markers, posing statistical and computational challenges.
  • Linked markers can significantly increase the power of mixture analysis.
  • Some forensic cases unsolvable with unlinked markers become solvable with linked markers.

Conclusions:

  • The proposed framework accommodates complex relationships and marker linkage in DNA mixture analysis.
  • Linked markers offer a substantial advantage in forensic genetics, especially for challenging cases.
  • Understanding linkage disequilibrium is crucial for accurate likelihood ratio calculations.