[Forum SIS] Avviso di seminario :: Mortera a DSS (Scienze Statistiche, Sapienza)

[Pierpaolo Brutti]

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 A v v i s o   d i   S e m i n a r i o
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Venerdì 21 Febbraio, ore 11am
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Stanza 34
Dipartimento di Scienze Statistiche
Sapienza Università di Roma

JULIA MORTERA
(Fac. di Economia, Università degli Studi di Roma3)

terrà un seminario dal titolo

ANALYSIS OF FORENSIC DNA MIXTURES

tutti gli interessati sono invitati a partecipare.

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Maggiori informazioni sui seminari presso il DSS sono
consultabili a quest'indirizzo: http://goo.gl/Y6OQYm

Saluti

Pierpaolo Brutti - Fulvio De Santis

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Summary

DNA is now routinely used in criminal investigations and court cases,
although DNA samples taken at crime scenes are of varying quality and
therefore present challenging problems for their interpretation. We
present a statistical model for the quantitative peak information
obtained from an electropherogram (EPG) of a forensic DNA sample and
illustrate its potential use for the analysis of criminal cases. In
contrast to most previously used methods, we directly model the peak
height information and incorporates important artefacts associated
with the production of the EPG. Our model has a number of unknown
parameters, and we show that these can be estimated by the method of
maximum likelihood in the presence of  multiple unknown contributors,
and their approximate standard errors calculated; the computations
exploit a Bayesian network representation of the model.  A case
example from a UK trial, as reported in the literature, is used to
illustrate the efficacy and use of the model, both in finding
likelihood ratios to quantify the strength of evidence, and in the
deconvolution of mixtures for the purpose of finding likely profiles
of one or more unknown contributors to a DNA sample.
Our model is readily extended to simultaneous analysis of more than
one mixture as illustrated in a case example. We show that combination
of evidence from several samples may give an evidential strength close
to that of a single source trace and thus modelling of peak height
information provides for a potentially very efficient mixture
analysis.

Joint work with Robert Cowell, Therese Graversen and Steffen Lauritzen
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