DNA-evidence is often believed to be a damning evidence, which leaves no space for uncertainty. In reality it is very difficult to say to what degree some piece of evidence can support a case against a crime suspect. That’s why forensic experts need statistical models to give weight to DNA-evidence. PhD-candidate Giulia Cereda developed new models that will be especially useful for rare DNA-profiles in the evidence, and for unbalanced DNA-mixtures.
When a DNA-profile found at a crime scene matches a suspect’s DNA-profile, it is important to know how frequent this profile can be found in the general population. For example, the evidence weights more if a suspect’s DNA-profile matches only two other persons in the general population, compared to a hundred other persons. Since forensic scientists don’t have the DNA-profiles of all individuals, they use databases that contain DNA-profiles of a sample of the population.
But often forensic scientists find DNA-profiles that don’t match one of the profiles in the database, which is called a rare type match case. Cereda developed several statistical models to deal with these cases.
‘The use of accurate mathematical models for forensic DNA evidence is very important to give probabilistic weight to observation. Geneticists and mathematicians need to work together to improve forensic science’, she concludes.