Literature DB >> 21519119

Inferring the number of contributors to mixed DNA profiles.

David R Paoletti1, Dan E Krane, Michael L Raymer, Travis E Doom.   

Abstract

Forensic samples containing DNA from two or more individuals can be difficult to interpret. Even ascertaining the number of contributors to the sample can be challenging. These uncertainties can dramatically reduce the statistical weight attached to evidentiary samples. A probabilistic mixture algorithm that takes into account not just the number and magnitude of the alleles at a locus, but also their frequency of occurrence allows the determination of likelihood ratios of different hypotheses concerning the number of contributors to a specific mixture. This probabilistic mixture algorithm can compute the probability of the alleles in a sample being present in a 2-person mixture, 3-person mixture, etc. The ratio of any two of these probabilities then constitutes a likelihood ratio pertaining to the number of contributors to such a mixture.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21519119     DOI: 10.1109/TCBB.2011.76

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  4 in total

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

Authors:  Torben Tvedebrink
Journal:  Int J Legal Med       Date:  2013-12-14       Impact factor: 2.686

2.  Genetic similarity of biological samples to counter bio-hacking of DNA-sequencing functionality.

Authors:  Mohd Siblee Islam; Stepan Ivanov; Eric Robson; Tríona Dooley-Cullinane; Lee Coffey; Kevin Doolin; Sasitharan Balasubramaniam
Journal:  Sci Rep       Date:  2019-06-18       Impact factor: 4.379

3.  Uncertainty in estimating the number of contributors from simulated DNA mixture profiles, with and without allele dropout, from Chinese, Malay, Indian, and Caucasian ethnic populations.

Authors:  Kevin Wai Yin Chong; Christopher Kiu-Choong Syn
Journal:  Sci Rep       Date:  2021-03-04       Impact factor: 4.996

Review 4.  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

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.