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SUMMARY:Evaluation of forensic DNA profiles while accounting for one and t
 wo repeat less and two repeat more stutters - Roberto Puch-Solis ()
DTSTART:20161109T093000Z
DTEND:20161109T101500Z
UID:TALK68890@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>Co-author: Dr Therese Graversen (University of  Copenhag
 en) <br></span> <br>Current forensic DNA profile technology is very sensit
 ive and can produce  profiles from a minute amount of DNA\, e.g. from one 
 cell. A profile from a stain  recovered from a crime scene is represented 
 through an electropherogram (epg)\,  which consists of peaks located in po
 sitions corresponding to alleles. Peak  heights are related to the origina
 ting amount of DNA: the more DNA the sample  contains\, the taller the pea
 ks are. <br> <br>An epg also tends to contain artefactual peaks of differe
 nt kinds. Some of  these artefacts originate during PCR duplication and ar
 e usually called  &lsquo\;stutters&rsquo\;. The most predominant of the st
 utter appears one STR less to the  corresponding alleles and it is about 1
 0% of the height of the allelic peak\,  although this percentage vary from
  locus to locus. Given the sensitivity of the  DNA systems\, other stutter
 s also tend to appear in the epg: one located two STR  less and the other 
 one STR more of the allelic peak. They tend to be much  smaller than their
  corresponding one STR less stutters. <br> <br>Many stain profiles from sa
 mples taken from a scene of a crime originate from  more than one person w
 here each of them contributes different amounts of DNA.  The peaks of mino
 r contributors can be about the same height of the stutters of  a major co
 ntributor. A stutter could also combine with an allelic peak or with  othe
 r stutters\, making an evaluation more complicated. Caseworkers are also  
 scrutinised on their stutters designations in court. <br> <br>Graversen & 
 Lauritzen (2015) introduced an efficient method for  calculating likelihoo
 d ratios using Bayesian Networks. In this talk\, this method  is extended 
 to consider two STR less and one STR more stutters\, and the  complexities
  of the extension is discussed. <br> <br>Reference <br> <span><br>Graverse
 n T. & Lauritzen S. (2015). Computational aspects of DNA mixture  analysis
 : exact inference using auxiliary variables in a Bayesian network.  Statis
 tics & Computing 25\, pp. 527-541.&nbsp\;</span>
LOCATION:Seminar Room 1\, Newton Institute
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