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    A Signal Model for Forensic DNA Mixtures


    Monich, Ulrich J. and Grgicak, Catherine and Cadambe, Viveck and Wu, Jason Yonglin and Wellner, Genevieve and Duffy, Ken R. and Medard, Muriel (2014) A Signal Model for Forensic DNA Mixtures. In: Asilomar Conference on Signals, Systems & Computers, 2-5 November 2014, Pacific Grove, California.

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    Abstract

    For forensic purposes, short tandem repeat allele signals are used as DNA fingerprints. The interpretation of signals measured from samples has traditionally been conducted by applying thresholding. More quantitative approaches have recently been developed, but not for the purposes of identifying an appropriate signal model. By analyzing data from 643 single person samples, we develop such a signal model. Three standard classes of two-parameter distributions, one symmetric (normal) and two right-skewed (gamma and log-normal), were investigated for their ability to adequately describe the data. Our analysis suggests that additive noise is well modeled via the log-normal distribution class and that variability in peak heights is well described by the gamma distribution class. This is a crucial step towards the development of principled techniques for mixed sample signal deconvolution.

    Item Type: Conference or Workshop Item (Paper)
    Keywords: Signal Model; Forensic; DNA Mixtures; DNA Fingerprints; short tandem repeat allele signals;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 5981
    Depositing User: Dr Ken Duffy
    Date Deposited: 24 Mar 2015 17:03
    Refereed: Yes
    URI:

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