Testing whether stutter and low-level DNA peaks are additive

John S. Buckleton, Kirk E. Lohmueller, Keith Inman, Kevin Cheng, James M. Curran, Simone N. Pugh, Jo Anne Bright, Duncan A. Taylor

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    Peaks in an electropherogram could represent alleles, stutter product, or a combination of allele and stutter. Continuous probabilistic genotyping (PG) systems model the heights of peaks in an additive manner: for a shared or composite peak, PG models assume that the peak height is the sum of the allelic component and the stutter component. In this work we examine the assumption that the heights of overlapping alleles from a minor contributor and stutter peaks from a major contributor are additive. Any peak below the analytical threshold is considered unobserved; hence, in any dataset and particularly in low-template DNA profiles, some or many peaks may be unobserved or missing. Using simulation and empirical data, we show that an additive model can explain the heights of overlapping alleles from a minor contributor and stutter peaks from a major contributor as long as missing data are carefully considered. We use a naive method of imputation for the missing data which appears to perform adequately in this case. If missing data are ignored then the sum of stutter and allelic peaks is expected to be an overestimate of the average height of the composite peaks, as was observed in this study.

    Original languageEnglish
    Article number102166
    Number of pages5
    JournalForensic Science International: Genetics
    Volume43
    DOIs
    Publication statusPublished - Nov 2019

    Keywords

    • Additivity
    • Allele
    • Low-template DNA
    • Missing data
    • Stacking
    • Stutter

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