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SUMMARY:Paternity testing and other inference about relationships from DNA
  mixtures - Julia Mortera (Università degli Studi Roma Tre)
DTSTART:20160926T123000Z
DTEND:20160926T131500Z
UID:TALK67582@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:DNA is now routinely used in criminal&nbsp\; and civil investi
 gations.&nbsp\; DNA samples are of varying quality and therefore present c
 hallenging problems for their interpretation. We present a statistical mod
 el for the quantitative peak information obtained from an electropherogram
  (EPG) of a forensic DNA sample and illustrate its potential use for the a
 nalysis of civil and criminal cases. In contrast to most previously used m
 ethods\, we directly model the peak height information and incorporate imp
 ortant artefacts associated with the production of the EPG. The model has 
 a number of unknown parameters\, that&nbsp\; can be estimated in the prese
 nce of multiple unknown contributors\; the computations exploit a Bayesian
  network&nbsp\;&nbsp\; representation of the model. <br><br>We illustrate 
 real casework examples from a criminal case and a disputed paternity case\
 , where in both cases part of the evidence was from a DNA mixture.&nbsp\;&
 nbsp\; We present methods for inference about the relationships between co
 ntributors to a DNA mixture of unknown genotype and other individuals of k
 nown genotype: a basic example would be testing whether a contributor to a
  mixture is the father of a child of known genotype (or indeed the similar
  question with the roles of parent and child reversed). Following commonly
  accepted practice\, the evidence for such a relationship is presented as 
 the likelihood ratio for the specified relationship versus the alternative
  that there is no such relationship\, so the father is taken to be a rando
 m member of the population. Our methods are based on the statistical model
  for DNA mixtures\, in which a Bayesian network is used as a computational
  device for efficiently computing likelihoods\; the present work builds on
  that approach\, but makes more explicit use of the BN in the modelling.<b
 r>&nbsp\;<br>Based on joint work with Peter Green.<br>
LOCATION:Seminar Room 1\, Newton Institute
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