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Forensic Sci Int Genet. 2019 Jan;38:219-224. doi: 10.1016/j.fsigen.2018.11.009. Epub 2018 Nov 11.

Probabilistic genotyping software: An overview.

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Center for Human Identification, Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX 76107, USA. Electronic address:
Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142 New Zealand.


The interpretation of mixed profiles from DNA evidentiary material is one of the more challenging duties of the forensic scientist. Traditionally, analysts have used a "binary" approach to interpretation where inferred genotypes are either included or excluded from the mixture using a stochastic threshold and other biological parameters such as heterozygote balance, mixture ratio, and stutter ratios. As the sensitivity of STR multiplexes and capillary electrophoresis instrumentation improved over the past 25 years, coupled with the change in the type of evidence being submitted for analysis (from high quality and quantity (often single-source) stains to low quality and quantity (often mixed) "touch" samples), the complexity of DNA profile interpretation has equally increased. This review provides a historical perspective on the movement from binary methods of interpretation to probabilistic methods of interpretation. We describe the two approaches to probabilistic genotyping (semi-continuous and fully continuous) and address issues such as validation and court acceptance. Areas of future needs for probabilistic software are discussed.


DNA mixture; Forensic DNA; Interpretation; Mixture software; Probabilistic genotyping; Validation

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