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TrueAllele® interpretation of DNA mixture evidence

M.W. Perlin, "TrueAllele® interpretation of DNA mixture evidence", Keynote talk, 9th International Conference on Forensic Inference and Statistics, Leiden University, The Netherlands, 20-Aug-2014.


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Abstract

A DNA mixture arises when two or more individuals contribute their DNA to biological evidence. STR data derived from this evidence contain peaks whose heights are in rough proportion to the genotype contributions1,2. The peak height data patterns at each genetic locus can be described by a hierarchical Bayesian model, which accounts for the genotypes, their relative quantities, PCR amplification and detection artifacts, and uncertainty in the data and variables.

The interpretation task is to objectively infer genotypes from the data, representing uncertainty as posterior probability. Comparison can be made afterwards between inferred genotypes to calculate a likelihood ratio (LR) that assesses evidential value3.

Cybergenetics TrueAllele® Casework system frames the STR data generation process in a hierarchical model4. First developed in the late 1990s, the TrueAllele model evolved through 25 versions as new explanatory variables were included or refined, and more hierarchical layers were added for robustness. Markov chain Monte Carlo (MCMC) was introduced early on to statistically solve probability equations of increasing dimensionality.

The system is designed around a fast and efficient forensic analyst workflow. A visual user interface (VUIer™) client program lets a user examine data, ask mixture questions, review genotype answers, and calculate LRs5,6. MCMC genotyping is done on parallel server computers connected to a coordinating TrueAllele database. All genotypes are uploaded to the database, and can be automatically compared with LR assessment for investigative applications. A small lab system can process hundreds of mixture items every day.

TrueAllele has been tested with diverse STR kits and instruments in over twenty validation studies, on both laboratory and casework samples4,7,9,10. The mixture samples contain up to five contributors, have high or low template amounts, may exhibit differential degradation, and can include relatives. log(LR) match comparisons show that TrueAllele is highly sensitive, specific and reproducible. Identification information varies predictably with DNA contributor amount, regardless of contributor number. With a sufficient number of assumed contributors, LR values remain constant.

TrueAllele has processed mixture items in hundreds of criminal cases8, including the World Trade Center disaster. Giving evidence in court entails educating lawyers and jurors about genotype inference and LRs before stating statistical results5. TrueAllele has been admitted into evidence after challenge in the United States and the United Kingdom.

The talk will describe the system's operation in the context of a criminal case, as it proceeds from DNA mixture interpretation through trial testimony.


References

  1. Perlin MW, Lancia G, Ng S-K. Toward fully automated genotyping: genotyping microsatellite markers by deconvolution. Am J Hum Genet. 1995;57(5):1199-210.
  2. Perlin MW, Szabady B. Linear mixture analysis: a mathematical approach to resolving mixed DNA samples. J Forensic Sci. 2001;46(6):1372-7.
  3. Perlin MW, Kadane JB, Cotton RW. Match likelihood ratio for uncertain genotypes. Law, Probability and Risk. 2009;8(3):289-302.
  4. Perlin MW, Sinelnikov A. An information gap in DNA evidence interpretation. PLoS ONE. 2009;4(12):e8327.
  5. Perlin MW. Explaining the likelihood ratio in DNA mixture interpretation. Twenty First International Symposium Human Ident, 2010; San Antonio, TX.
  6. Perlin MW. Sherlock Holmes and the DNA likelihood ratio (A142). AAFS 63rd Annual Scientific Meeting; Chicago, IL. Amer Acad Forensic Sci; 2011. p. 95.
  7. Perlin MW, Legler MM, Spencer CE, Smith JL, Allan WP, Belrose JL, Duceman BW. Validating TrueAllele® DNA mixture interpretation. J Forensic Sci. 2011;56(6):1430-47.
  8. Perlin MW. When good DNA goes bad. J Forensic Res. 2013; S11:003.
  9. Ballantyne J, Hanson EK, Perlin MW. DNA mixture genotyping by probabilistic computer interpretation of binomially-sampled laser captured cell populations: Combining quantitative data for greater identification information. Sci Justice. 2013;53(2):103-14.
  10. Perlin MW, Belrose JL, Duceman BW. New York State TrueAllele® Casework validation study. J Forensic Sci. 2013;58(6):1458-66.

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