Abstract
Probabilistic genotyping systems endeavor to aid human analysts in the interpretation of complex DNA mixtures. Laboratories use these complicated programs to attach statistical weights to results from evidence samples that cannot be confirmed by analysts using manual/conventional approaches. Before relying on these systems in case work, it is essential that the software be subjected to rigorous internal validation that establishes the limits of their reliability. Complex mixtures encountered in casework often have attributes that make interpretation challenging, including low template levels, unknown/high number of contributors, high levels of allele sharing, differential degradation, and so forth. Each laboratory’s internal validation should critically evaluate its performance using the system on samples that mimic or exceed the complexity with respect to these potential attributes, both individually and collectively of those encountered in the laboratory’s casework. The results of carefully designed internal validation experiments must not only demonstrate a system’s utility but also clearly establish and articulate the limits of reliability for use in casework.
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Krane, D.E., Philpott, M.K. (2022). Using Laboratory Validation to Identify and Establish Limits to the Reliability of Probabilistic Genotyping Systems. In: Dash, H.R., Shrivastava, P., Lorente, J.A. (eds) Handbook of DNA Profiling. Springer, Singapore. https://doi.org/10.1007/978-981-16-4318-7_10
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