Some probabilistic mixture programmes take into account the presence of additional alleles by utilising drop-in models [1-4]. Although the precise details of the various models vary, at their core, they all rely on two basic assumptions - (1) that drop-in events occur independently of each other and (2) the frequency of individual dropped-in alleles mirrors the composition within some specified population. In order to examine the robustness of these assumptions, we have collected data on allele drop-in and contamination events in 28,842 negative control samples processed over a three year period in our DNA crime laboratory. These data were used to characterise drop-in events, and to identify trends in drop-in rates over time and between control types. In addition, we carried out an experiment using genomic DNA that had been highly diluted and demonstrate that, at these levels, drop-in events become indistinguishable from low level genomic contamination. Our results show that drop-in alleles are not necessarily independent random events. Moreover, a comparison between our data and UK frequency databases also suggests that the frequency of individual dropped-in alleles does not mirror the general population frequencies.
Keywords: Contamination; DNA analysis; Drop-in.
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