PopAffiliator: online calculator for individual affiliation to a major population group based on 17 autosomal short tandem repeat genotype profile View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-09

AUTHORS

Luísa Pereira, Farida Alshamali, Rune Andreassen, Ruth Ballard, Wasun Chantratita, Nam Soo Cho, Clotilde Coudray, Jean-Michel Dugoujon, Marta Espinoza, Fabricio González-Andrade, Sibte Hadi, Uta-Dorothee Immel, Catalin Marian, Antonio Gonzalez-Martin, Gerhard Mertens, Walther Parson, Carlos Perone, Lourdes Prieto, Haruo Takeshita, Héctor Rangel Villalobos, Zhaoshu Zeng, Lev Zhivotovsky, Rui Camacho, Nuno A. Fonseca

ABSTRACT

Because of their sensitivity and high level of discrimination, short tandem repeat (STR) maker systems are currently the method of choice in routine forensic casework and data banking, usually in multiplexes up to 15-17 loci. Constraints related to sample amount and quality, frequently encountered in forensic casework, will not allow to change this picture in the near future, notwithstanding the technological developments. In this study, we present a free online calculator named PopAffiliator ( http://cracs.fc.up.pt/popaffiliator ) for individual population affiliation in the three main population groups, Eurasian, East Asian and sub-Saharan African, based on genotype profiles for the common set of STRs used in forensics. This calculator performs affiliation based on a model constructed using machine learning techniques. The model was constructed using a data set of approximately fifteen thousand individuals collected for this work. The accuracy of individual population affiliation is approximately 86%, showing that the common set of STRs routinely used in forensics provide a considerable amount of information for population assignment, in addition to being excellent for individual identification. More... »

PAGES

629-636

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00414-010-0472-2

DOI

http://dx.doi.org/10.1007/s00414-010-0472-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1033195854

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20552217


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