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    A large-scale dataset of single and mixed-source short tandem repeat profiles to inform human identification strategies: PROVEDIt


    Alfonse, Lauren E., Garrett, Amanda D., Lun, Desmond S., Duffy, Ken R. and Grgicak, Catherine (2018) A large-scale dataset of single and mixed-source short tandem repeat profiles to inform human identification strategies: PROVEDIt. Forensic Science International: Genetics, 32. pp. 62-70. ISSN 1878-0326

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    Abstract

    DNA-based human identity testing is conducted by comparison of PCR-amplified polymorphic Short Tandem Repeat (STR) motifs from a known source with the STR profiles obtained from uncertain sources. Samples such as those found at crime scenes often result in signal that is a composite of incomplete STR profiles from an unknown number of unknown contributors, making interpretation an arduous task. To facilitate advancement in STR interpretation challenges we provide over 25,000 multiplex STR profiles produced from one to five known individuals at target levels ranging from one to 160 copies of DNA. The data, generated under 144 laboratory conditions, are classified by total copy number and contributor proportions. For the 70% of samples that were synthetically compromised, we report the level of DNA damage using quantitative and end-point PCR. In addition, we characterize the complexity of the signal by exploring the number of detected alleles in each profile.
    Item Type: Article
    Keywords: Forensic DNA; PROVEDIt; STRs; Human identification; STR database;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 13074
    Identification Number: 10.1016/j.fsigen.2017.10.006
    Depositing User: Dr Ken Duffy
    Date Deposited: 19 Jun 2020 15:14
    Journal or Publication Title: Forensic Science International: Genetics
    Publisher: Elsevier
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/13074
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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