Sala Grande - 19th IAFS World Meeting - 9th WPMO Triennial Meeting

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Author(s): Corradi F 1
19 th IAFS WORLD MEETING
9 th WPMO TRIENNIAL MEETING
5 th MAFS MEETING
EVALUATION OF KINSHIP IDENTIFICATION SYSTEMS BASED ON STR DNA PROFILES
Institution(s): 1 DEPARTMENT OF STATISTICS UNIVERSITY OF FLORENCE, ITALY
Introduction: Our interest is in personal identification through DNA evidence, more precisely in kinship analysis based on STR loci
markers. Genetic evidence is used to establish whether a certain person (named candidate) occupies a specific position in a familial
pedigree or is a random person from the population. The aim of the research is to evaluate the identification system performance
before carrying out an identification trial. We want to give guidelines for planning an identification experiment for what concerns the
number and the identity of the familial donors of genetic evidence and the number and type of loci used as markers.
Methods: The starting point of our proposal for the system evaluation consists in the masking of the genetic evidence of the candidate,
and thus considering the LR as random variable, varying conditionally on which hypothesis is assumed to hold. Our proposal is to
measure the expected loss for each identification system by the probability of giving support to the hypothesis that is not assumed to
hold. We want also to consider how some violations to standard assumption1 for population or segregation models (i.e. Hardy-
Weinberg equilibrium and Mendelian Segregation laws), such as coancestry, identity by descent, inbreeding or uncertainty in allele
frequency in the population, affect the expected performance of the identification system. Bayesian Networks were used to make
inference by probability propagation methods. The flexibility of the BNs is helpful to introduce complexity due to violation of standard
assumptions. To handle the huge dimensionality of the probability distributions involved and to correctly treat the various sources of
uncertainty implied, the use of MC or MCMC simulation methods was required to make our proposal computationally tractable. This
methodology has been applied to a real case study, concerning a very indirect identification, which seems to take advantage of it.
Final Comments: Even if the LR depends on the whole available evidence, we demonstrate that its distributions only depend on the
genotype of the candidate, conditionally on the evidence provided by the family donors. Taking into account Daubert vs Merrell Dow
Pharmaceuticals sentence2, which requires that a scientific technique should have known error rates and standard of performance to
be considered valuable in a court of justice, our proposal applies this principle and should be carried out every time a kinship
identification is attempted. The proposed technique allows us also to specify the required performance of the identification experiment
for any specific case, according for instance to the civil or criminal nature of the trial. Currently standards of performance are only
required for laboratory procedures but they are not defined to assess the effectiveness of the information for identification
experiments. In our opinion, this lack of legislature has to be corrected and legislative proposals could be put forward following
suggestion from this work and future developments. There are only few studies concerning the evaluation of the identification system.
However, unlike our work, they are not case-specific and propose measure of loss not related to the expected error rates of the system.
Keywords: Kinship Identification; DNA STR Markers; Likelihood Ratio Distribution; Bayesian Networks