Literature DB >> 24337321

On the exact distribution of the numbers of alleles in DNA mixtures.

Torben Tvedebrink1.   

Abstract

When more than one individual contributes biological material to a forensic stain, the resulting DNA type is termed a DNA mixture. DNA mixtures occur frequently in forensic genetic casework, and in recent years, much research has been devoted to this subject. This paper presents a derivation of the exact distribution of the number of alleles for any number of profiles and investigated loci. The per locus number of observed alleles is of interest as it indicates the plausible range on the number of contributors. Hence, by specifying a prior distribution on the number of contributors, the locus distribution may be used to assess the number of contributors. Furthermore, the total number of alleles across all loci is used by some forensic geneticists to estimate the probability that an allele has failed to be detected (allelic drop-out).

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Year:  2013        PMID: 24337321     DOI: 10.1007/s00414-013-0951-3

Source DB:  PubMed          Journal:  Int J Legal Med        ISSN: 0937-9827            Impact factor:   2.686


  12 in total

1.  Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

Authors:  A Biedermann; S Bozza; K Konis; F Taroni
Journal:  Forensic Sci Int Genet       Date:  2012-04-24       Impact factor: 4.882

2.  Empirical analysis of the STR profiles resulting from conceptual mixtures.

Authors:  David R Paoletti; Travis E Doom; Carissa M Krane; Michael L Raymer; Dan E Krane
Journal:  J Forensic Sci       Date:  2005-11       Impact factor: 1.832

3.  LoComatioN: a software tool for the analysis of low copy number DNA profiles.

Authors:  Peter Gill; Amanda Kirkham; James Curran
Journal:  Forensic Sci Int       Date:  2006-06-08       Impact factor: 2.395

4.  Towards understanding the effect of uncertainty in the number of contributors to DNA stains.

Authors:  John S Buckleton; James M Curran; Peter Gill
Journal:  Forensic Sci Int Genet       Date:  2006-12-11       Impact factor: 4.882

5.  THE RARITY OF DNA PROFILES.

Authors:  Bruce S Weir
Journal:  Ann Appl Stat       Date:  2007       Impact factor: 2.083

6.  Inferring the number of contributors to mixed DNA profiles.

Authors:  David R Paoletti; Dan E Krane; Michael L Raymer; Travis E Doom
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2011-04-18       Impact factor: 3.710

7.  Statistical model for degraded DNA samples and adjusted probabilities for allelic drop-out.

Authors:  Torben Tvedebrink; Poul Svante Eriksen; Helle Smidt Mogensen; Niels Morling
Journal:  Forensic Sci Int Genet       Date:  2011-04-01       Impact factor: 4.882

8.  Analysis of matches and partial-matches in a Danish STR data set.

Authors:  Torben Tvedebrink; Poul Svante Eriksen; James Michael Curran; Helle Smidt Mogensen; Niels Morling
Journal:  Forensic Sci Int Genet       Date:  2011-09-06       Impact factor: 4.882

9.  Exploratory data analysis for the interpretation of low template DNA mixtures.

Authors:  H Haned; K Slooten; P Gill
Journal:  Forensic Sci Int Genet       Date:  2012-09-13       Impact factor: 4.882

10.  A new methodological framework to interpret complex DNA profiles using likelihood ratios.

Authors:  P Gill; H Haned
Journal:  Forensic Sci Int Genet       Date:  2012-12-14       Impact factor: 4.882

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  2 in total

1.  MaSTR™: an effective probabilistic genotyping tool for interpretation of STR mixtures associated with differentially degraded DNA.

Authors:  Mitchell M Holland; Teresa M Tiedge; Abigail J Bender; Sidney A Gaston-Sanchez; Jennifer A McElhoe
Journal:  Int J Legal Med       Date:  2022-01-29       Impact factor: 2.686

Review 2.  A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™.

Authors:  Peter Gill; Corina Benschop; John Buckleton; Øyvind Bleka; Duncan Taylor
Journal:  Genes (Basel)       Date:  2021-09-30       Impact factor: 4.096

  2 in total

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