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Related Experiment Videos

Matching and partially-matching DNA profiles.

Bruce S Weir1

  • 1Program in Statistical Genetics, Department of Statistics, North Carolina State University, Raleigh, NC 7695-7566, USA.

Journal of Forensic Sciences
|October 6, 2004
PubMed
Summary

DNA profile matching probabilities are influenced by allele frequencies and population structure. Analysis of FBI and Australian databases shows good agreement, suggesting that relatedness can be inferred even between unrelated individuals.

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Area of Science:

  • Forensic Science
  • Population Genetics
  • Statistical Analysis

Background:

  • DNA profiles allow for comparison of genetic information between individuals.
  • The number of matching alleles between two DNA profiles can vary (0, 1, or 2 pairs per locus).
  • Probabilities of these matches are influenced by allele frequencies and population structure (theta).

Purpose of the Study:

  • To evaluate the agreement between observed and expected DNA profile match statistics in forensic databases.
  • To assess the impact of population structure on likelihood ratios for relatedness.
  • To predict database sizes required for identifying individuals with a high number of matching loci.

Main Methods:

  • Statistical analysis of DNA profile data from FBI and Australian databases.

Related Experiment Videos

  • Calculation of match, partial match, and mismatch probabilities considering allele frequencies and theta.
  • Computation of likelihood ratios to assess relatedness hypotheses.

    • Main Results:

    • Observed and expected numbers of matching/partially matching loci showed good agreement in databases when theta was a small positive value.
    • Likelihood ratios supporting relatedness can occur even for unrelated individuals.
    • Predictions indicate that databases are likely to already contain pairs with numerous matching loci (e.g., >=9 among 13 CODIS loci).

    Conclusions:

    • The statistical model accurately describes DNA profile comparisons in real-world forensic databases.
    • Population structure parameter theta plays a role in accurately interpreting DNA match statistics.
    • The likelihood of finding pairs with significant DNA profile overlap increases with database size.