Total allele count distribution (TAC curves) improves number of contributor estimation for complex DNA mixtures

References

• Buckleton JS, Curran JM. A discussion of the merits of random man not excluded and likelihood ratios. Forensic Sci Int Genet. 2008;2(4):343–348.
   PubMed Web of Science ®Google Scholar
• Budowle B, Onorato AJ, Callaghan TF, et al. Mixture interpretation: defining the relevant features for guidelines for the assessment of mixed DNA profiles in forensic casework. J Forensic Sci. 2009;54(4):810–821.
   PubMed Web of Science ®Google Scholar
• Gill P, Whitaker J, Flaxman C, et al. An investigation of the rigor of interpretation rules for STR’s derived from less that 100 pg of DNA. Forensic Sci Int. 2000;112(1):17–40.
   PubMed Web of Science ®Google Scholar
• Gill P, Brenner CH, Buckleton JS, DNA commission of the International Society of Forensic Genetics, et al. DNA commission of the International Society of Forensic Genetics: Recommendations on the interpretation of mixtures. Forensic Sci Int. 2006;160(2-3):90–101.
   PubMed Web of Science ®Google Scholar
• Gill P, Haned H, Bleka Ø, et al. Genotyping and interpretation of STR-DNA: Low-template, mixtures and database matches-Twenty years of research and development. Forensic Sci Int Genet. 2015;18:100–117.
   PubMed Web of Science ®Google Scholar
• Ladd C, Lee HC, Yang N, et al. Interpretation of complex forensic DNA mixtures. Croat Med J. 2001;42(3):244–246.
   PubMed Web of Science ®Google Scholar
• Curran JM, Buckleton JS. Inclusion probabilities and dropout. J Forensic Sci. 2010;55(5):1171–1173.
   PubMed Web of Science ®Google Scholar
• Gill P, Gusmão L, Haned H, et al. DNA commission of the International Society of Forensic Genetics: recommendations on the evaluation of STR typing results that may include drop-out and/or drop-in using probabilistic methods. Forensic Sci Int Genet. 2012;6(6):679–688.
   PubMed Web of Science ®Google Scholar
• Bieber FR, Buckleton JS, Budowle B, et al. Evaluation of forensic DNA mixture evidence: protocol for evaluation, interpretation, and statistical calculations using the combined probability of inclusion. BMC Genet. 2016;17(1):125doi: 10.1186/s12863-016-0429-7.
   PubMedGoogle Scholar
• President’s Council of Advisors on Science and Technology, PCAST releases Report on Forensic Science in Criminal Courts. 2016.
   Google Scholar
• Butler JM, Kline MC, Coble MD. NIST interlaboratory studies involving DNA mixtures (MIX05 and MIX13): variation observed and lessons learned. Forensic Sci Int Genet. 2018;37:81–94.
   PubMed Web of Science ®Google Scholar
• Perlin MW, Legler MM, Spencer CE, et al. Validating TrueAllele® DNA mixture interpretation. J. Forensic Sci. 2011;56:1–18.
   Web of Science ®Google Scholar
• Gill P, Haned H. A new methodological framework to interpret complex DNA profiles using likelihood ratios. Forensic Sci Int Genet. 2013;7(2):251–263.
   PubMed Web of Science ®Google Scholar
• Taylor D, Bright JA, Buckleton JS. The interpretation of single source and mixed DNA profiles. Forensic Sci Int Genet. 2013;7(5):516–528.
   PubMed Web of Science ®Google Scholar
• Inman K, Rudin N, Cheng K, et al. Lab Retriever: a software tool for calculating likelihood ratios incorporating a probability of drop-out for forensic DNA profiles. BMC Bioinform. 2015;16:298.
   PubMed Web of Science ®Google Scholar
• Bleka Ø, Storvik G, Gill P. EuroForMix: an open source software based on a continuous model to evaluate STR DNA profiles from a mixture of contributors with artefacts. Forensic Sci Int Genet. 2016;21:35–44.
   PubMed Web of Science ®Google Scholar
• Kelly H, Bright JA, Buckleton JS, et al. A comparison of statistical models for the analysis of complex forensic DNA profiles. Sci Justice. 2014;54(1):66–70.
   PubMed Web of Science ®Google Scholar
• Bright JA, Taylor D, McGovern C, et al. Developmental validation of STRmix™, expert software for the interpretation of forensic DNA profiles. Forensic Sci Int Genet. 2016;23:226–239.
   PubMed Web of Science ®Google Scholar
• Buckleton JS, Bright JA, Cheng K, et al. NIST interlaboratory studies involving DNA mixtures (MIX13): A modern analysis. Forensic Sci Int Genet. 2018;37:172–179.
   PubMed Web of Science ®Google Scholar
• Bright JA, Cheng K, Kerr Z, et al. STRmix™ collaborative exercise on DNA mixture interpretation. Forensic Sci Int Genet. 2019;40:1–8.
   PubMed Web of Science ®Google Scholar
• Haned H, Péne L, Sauvage F, et al. The predictive value of the maximum likelihood estimator of the number of contributors to a DNA mixture. Forensic Sci Int Genet. 2011;5(4):281–284.
   PubMed Web of Science ®Google Scholar
• Bright JA, Curran JM, Buckleton JS. The effect of the uncertainty in the number of contributors to mixed DNA profiles on profile interpretation. Forensic Sci Int Genet. 2014;12:208–214.
   PubMed Web of Science ®Google Scholar
• Curran JM, Buckleton JS. Uncertainty in the number of contributors for the European standard set of loci. Forensic Sci Int Genet. 2014;11:205–206.
   PubMed Web of Science ®Google Scholar
• Taylor D, Bright JA, Buckleton JS. Interpreting forensic DNA profiling evidence without specifying the number of contributors. Forensic Sci Int Genet. 2014;13:269–280.
   PubMed Web of Science ®Google Scholar
• Benschop CCG, van der Beek CP, Meiland HC, et al. Low template STR typing: Effect of replicate number and consensus method on genotyping reliability and DNA database search results. Forensic Sci Int Genet. 2011;5(4):316–328.
   PubMed Web of Science ®Google Scholar
• Moretti TR, Just RS, Kehl SC, et al. Internal validation of STRmix™ for the interpretation of single source and mixed DNA profiles. Forensic Sci Int Genet. 2017;29:126–144.
   PubMed Web of Science ®Google Scholar
• Bright JA, Richards R, Kruijver M, et al. Internal validation of STRmixTM – a multi laboratory response to PCAST. Forensic Sci. Int. Genet. 2018;34:11–24.
   PubMed Web of Science ®Google Scholar
• Bille T, Weitz S, Buckleton JS, et al. Interpreting a major component from a mixed DNA profile with an unknown number of minor contributors. Forensic Sci Int Genet. 2019;40:150–159.
   PubMed Web of Science ®Google Scholar
• Coble MD, Bright JA, Buckleton JS, et al. Uncertainty in the number of contributors in the proposed new CODIS set. Forensic Sci Int Genet. 2015;19:207–211.
   PubMed Web of Science ®Google Scholar
• Clayton TM, Whitaker JP, Sparkes R, et al. Analysis and interpretation of mixed forensic stains using DNA STR profiling. Forensic Sci Int. 1998;91(1):55–70.
   PubMed Web of Science ®Google Scholar
• Biedermann A, Bozza S, Konis K, et al. Inference about the number of contributors to a DNA mixture: comparative analyses of a Bayesian network approach and the maximum allele count method. Forensic Sci Int Genet. 2012;6(6):689–696.
   PubMed Web of Science ®Google Scholar
• Butler JM. Advanced topics in forensic DNA typing: Interpretation, low-level DNA and complex mixtures. Cambridge, MA: Academic Press; 2014.
   Google Scholar
• Paoletti DR, Doom TE, Krane CM, et al. Empirical analysis of the STR profiles resulting from conceptual mixtures. J Forensic Sci. 2005;50(6):1361–1366.
   PubMed Web of Science ®Google Scholar
• Buckleton JS, Curran JM, Gill P. Towards understanding the effect of uncertainty in the number of contributors to DNA stains. Forensic Sci Int Genet. 2007;1(1):20–28.
   PubMed Web of Science ®Google Scholar
• KWY, Syn CKC. Uncertainty in estimating the number of contributors from simulated DNA mixture profiles, with and without allele dropout, from Chinese, Malay, Indian, and Caucasian ethnic populations. Sci Rep. 2021;11:5249.
   PubMed Web of Science ®Google Scholar
• Paoletti DR, Krane DE, Raymer ML, et al. Inferring the number of contributors to mixed DNA profiles. IEEE/ACM Trans Comput Biol Bioinform. 2012;9(1):113–122.
   PubMed Web of Science ®Google Scholar
• Alfonse LE, Tejada G, Swaminathan H, et al. Inferring the number of contributors to complex DNA mixtures using three methods: Exploring the limits of low-template DNA interpretation. J Forensic Sci. 2017;62(2):308–316.
   PubMed Web of Science ®Google Scholar
• Kruijver M, Kelly H, Cheng K, et al. Estimating the number of contributors to a DNA profile using decision trees. Forensic Sci Int Genet. 2021;50:102407.
   PubMed Web of Science ®Google Scholar
• Benschop CCG, Van der Linden J, Hoogenboom J, et al. Automated estimation of the number of contributors in autosomal short tandem repeat profiles using a machine learning approach. Forensic Sci Int Genet. 2019;43:102150.
   PubMed Web of Science ®Google Scholar
• Grgicak CM, Karkar S, Yearwood-Garcia X, et al. A large-scale validation of NOCIt’s a posteriori probability of the number of contributors and its integration into forensic interpretation pipelines. Forensic Sci Int Genet. 2020;47:102296.
   PubMed Web of Science ®Google Scholar
• Marciano MA, Adelman JD. PACE: probabilistic assessment for contributor Estimation- A machine learning-based assessment of the number of contributors in DNA mixtures. Forensic Sci Int Genet. 2017;27:82–91.
   PubMed Web of Science ®Google Scholar
• Marciano MA, Adelman JD. Developmental validation of PACE™: Automated artifact identification and contributor estimation for use with GlobalFiler™ and PowerPlex® fusion 6c generated data. Forensic Sci Int Genet. 2019;43:102140.
   PubMed Web of Science ®Google Scholar
• Perez J, Mitchell AA, Ducasse N, et al. Estimating the number of contributors to two-, three-, and four-person mixtures containing DNA in high template and low template amounts. Croat Med J. 2011;52(3):314–326.
   PubMed Web of Science ®Google Scholar
• Tvedebrink T. On the exact distribution of the numbers of alleles in DNA mixtures. Int J Legal Med. 2014;128(3):427–437.
   PubMed Web of Science ®Google Scholar
• Hill CR, Duewer DL, Kline MC, et al. U.S. Population data for 29 autosomal STR loci. Forensic Sci Int Genet. 2013;7(3):e82–e3.
   PubMed Web of Science ®Google Scholar
• Steffen CR, Coble MD, Gettings KB, et al. Corrigendum to ‘U.S. Population Data for 29 Autosomal STR Loci’ [Forensic Sci. Int. Genet. 7 (2013) e82-e83]]. Forensic Sci Int Genet. 2017;31:e36–e40.
   PubMed Web of Science ®Google Scholar
• McCulloh KL, Ng J, Oldt RF, et al. The genetic structure of native Americans in North America based on the GlobalfilerÒSTRs. Leg Med (Tokyo). 2016;23:49–54.
   PubMed Web of Science ®Google Scholar
• National Research Council, The evaluation of forensic DNA Evidence. Washington, DC: National Academies Press; 1996.
   Google Scholar
• Alfonse LE, Garrett AD, Lun DS, et al. A large-scale dataset of single and mixed-source short tandem repeat profiles to inform human identification strategies: PROVEDIt. Forensic Sci Int Genet. 2018;32:62–70.
   PubMed Web of Science ®Google Scholar
• Marquis R, Biedermann A, Cadola L, et al. Discussion on how to implement a verbal scale in a forensic laboratory: Benefits, pitfalls and suggestions to avoid misunderstandings. Sci Justice. 2016;56(5):364–370.
   PubMed Web of Science ®Google Scholar
• Noël S, Noël J, Granger D, et al. STRmix™ put to the test: 300 000 non-contributor profiles compared to four-contributor DNA mixtures and the impact of replicates. Forensic Sci Int Genet. 2019;41:24–31.
   PubMed Web of Science ®Google Scholar
• Milot E, Baechler S, Crispino F. Must the random man be unrelated? A lingering misconception in forensic genetics. Forensic Sci Int Synerg. 2020;2:35–40.
   PubMedGoogle Scholar