Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Forensic genealogy-A comparison of methods to infer distant relationships based on dense SNP data
Oslo Univ Hosp, Norway.
Linköping University, Department of Clinical and Experimental Medicine, Division of Hematopoiesis and Developmental Biology. Linköping University, Faculty of Medicine and Health Sciences. Natl Board Forens Med, Dept Forens Genet and Forens Toxicol, Linkoping, Sweden.
2019 (English)In: Forensic Science International: Genetics, ISSN 1872-4973, E-ISSN 1878-0326, Vol. 42, p. 113-124Article in journal (Refereed) Published
Abstract [en]

The concept forensic genealogy was discussed already in 2005 but has recently emerged in relation to the use of public genealogy databases to find relatives of the donor of a crime stain. In this study we explored the results and evaluation of searches conducted in such databases. In particular, we focused on the statistical classification that entails from the search and study the variation observed for different relationship classes. The forensic guidelines advocate the use of the likelihood ratio (LR) as a mean to measure the weight of evidence, which requires exact formulation of competing hypotheses. We contrast the LR approach with alternative approaches relying on identical by state (IBS) measures to estimate the total length of shared genomic segments as well as identical by descent (IBD) coefficients for a pair of individuals. We used freely accessible data from the 1000 Genome project to perform extensive simulations, generating data for a number of distinct relationships. Specifically we studied some overarching relationship classes and the performance of the above-mentioned evaluative approaches to classify a known pair of relatives into each class. The results indicate that the traditional LR approach as a single source of classification is as good as, and in some cases even better than, the alternative approaches. In particular the true classification rate is higher for some distant relationship. However, the LR approach is both computer-intensive and sensitive to population frequencies as well as genetic maps (positions of the markers). We further showed that when combining different classification approaches, a lower false classification rate was achieved while still maintaining a high true classification rate.

Place, publisher, year, edition, pages
ELSEVIER IRELAND LTD , 2019. Vol. 42, p. 113-124
Keywords [en]
Forensic genealogy; SNP; Forensic statistics; Classification; Identity by descent
National Category
Genetics
Identifiers
URN: urn:nbn:se:liu:diva-160396DOI: 10.1016/j.fsigen.2019.06.019ISI: 000483955000020PubMedID: 31302460OAI: oai:DiVA.org:liu-160396DiVA, id: diva2:1353558
Available from: 2019-09-23 Created: 2019-09-23 Last updated: 2019-11-28

Open Access in DiVA

fulltext(3347 kB)5 downloads
File information
File name FULLTEXT01.pdfFile size 3347 kBChecksum SHA-512
765cd29754db5da46a91337822f63cdf60567587bbd8a9d518e9f3898efc4ed082ae8138d14a637c9584d39ad83d33d45cbfbffd9cf5568230bdd8b0e88b1079
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Tillmar, Andreas
By organisation
Division of Hematopoiesis and Developmental BiologyFaculty of Medicine and Health Sciences
In the same journal
Forensic Science International: Genetics
Genetics

Search outside of DiVA

GoogleGoogle Scholar
Total: 5 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 13 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf