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SUMMARY:Modeling subpopulations in a forensic DNA database using a latent 
 variable approach - Maarten Kruijver (None / Other\; Vrije Universiteit Am
 sterdam)
DTSTART:20161109T120000Z
DTEND:20161109T123000Z
UID:TALK69112@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Several problems in forensic genetics require a representative
  model of a forensic DNA database. Obtaining an accurate representation of
  the offender database can be difficult\, since databases typically contai
 n groups of persons with unregistered ethnic origins in unknown proportion
 s. We propose to estimate the allele frequencies of the subpopulations com
 prising the offender database and their proportions from the database itse
 lf using a latent variable approach. We present a model for which paramete
 rs can be estimated using the expectation maximization (EM) algorithm. Thi
 s approach does not rely on relatively small and possibly unrepresentative
  population surveys\, but is driven by the actual genetic composition of t
 he database only. We fit the model to a snapshot of the Dutch offender dat
 abase (2014)\, which contains close to 180\,000 profiles\, and find that t
 hree subpopulations suffice to describe a large fraction of the heterogene
 ity in the database. We demonstrate the utility and reliability of the app
 roach by using the model to predict the number of false leads obtained in 
 database searches. We assess how well the model predicts the number of fal
 se leads obtained in mock searches in the Dutch offender database\, both f
 or the case of familial searching for first degree relatives of a donor an
 d searching for contributors to three person mixtures. We also study the d
 egree of partial matching between all pairs of profiles in the Dutch datab
 ase and compare this to what is predicted using the latent variable approa
 ch.
LOCATION:Seminar Room 1\, Newton Institute
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