A tale of two PG systems: A comparison of the two most widely used continuous probabilistic genotyping systems in the United States
Corresponding Author
Susan A. Greenspoon PhD
Virginia Department of Forensic Science, Richmond, Virginia, USA
Correspondence
Susan A. Greenspoon, Virginia Department of Forensic Science, 700 North 5th Street, Richmond, VA 23219, USA.
Email: [email protected]
Search for more papers by this authorLisa Schiermeier-Wood MS
Virginia Department of Forensic Science, Richmond, Virginia, USA
Search for more papers by this authorBradford C. Jenkins MS
Virginia Department of Forensic Science, Richmond, Virginia, USA
Search for more papers by this authorCorresponding Author
Susan A. Greenspoon PhD
Virginia Department of Forensic Science, Richmond, Virginia, USA
Correspondence
Susan A. Greenspoon, Virginia Department of Forensic Science, 700 North 5th Street, Richmond, VA 23219, USA.
Email: [email protected]
Search for more papers by this authorLisa Schiermeier-Wood MS
Virginia Department of Forensic Science, Richmond, Virginia, USA
Search for more papers by this authorBradford C. Jenkins MS
Virginia Department of Forensic Science, Richmond, Virginia, USA
Search for more papers by this authorPresented in part at the Potomac Regional Symposium on Forensic DNA Analysis, October 2–4, 2023, in Fairfax, VA and at the 76th Annual Scientific Conference of the American Academy of Forensic Sciences, February 19–24, 2024, in Denver, CO.
Abstract
The development of probabilistic genotyping (PG) systems to quantitatively analyze DNA mixture samples has been transformative in forensic science. TrueAllele® Casework (TA) and STRmix™ (STRmix) are the two most widely used PG systems in the United States. The two systems were challenged with 48 two-, three-, and four-person mock casework samples, for a total of 152 likelihood ratio (LR) comparisons. TA and STRmix converged on the same result (supportive, non-supportive, or inconclusive) for ~91% of contributor-specific comparisons. Where moderate or substantial differences in log(LR) values were observed, 9% affected the conclusion of the reference association to the mixture. The PG systems exhibited high correlations for estimated contributor-specific template quantities (~92%) and log(LR)s produced (>88%). When the log(LR)s for only low-template contributors (<100 pg) were compared, the R2 value dropped to ~68% and the difference became statistically significant. Of the 14 contributor comparisons where the conclusion differed, two were contradictory (supportive vs. non-supportive) and 12 were either inconclusive versus non-supportive or inconclusive versus supportive. The differing results were likely due to dissimilarities in the mixture input file as STRmix uses a lab-defined analytical threshold (AT) and TA models to 10 RFUs for each electropherogram. When 7 of the 14 mixtures were reanalyzed by STRmix using a 10 RFU AT, the log(LR)s for the low-template contributors became more similar to TAs. This study shows that while both systems may produce accurate and calibrated LRs, their results can deviate, especially for low-template, degraded contributors, and the deviation is generally predictable.
CONFLICT OF INTEREST STATEMENT
The authors have no conflicts of interest to report.
Supporting Information
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REFERENCES
- 1Perlin MW, Szabady B. Linear mixture analysis: a mathematical approach to resolving mixed DNA samples. J Forensic Sci. 2001; 46(6): 1372–1378. https://doi.org/10.1520/JFS15158J
- 2Perlin MW, Sinelnikov A. An information gap in DNA evidence interpretation. PLoS One. 2009; 4(12):e8327. https://doi.org/10.1371/journal.pone.0008327
- 3Bright JA, Taylor D, McGovern C, Cooper S, Russell L, Abarno D, et al. Developmental validation of STRmix™, expert software for the interpretation of forensic DNA profiles. Forensic Sci Int Genet. 2016; 23: 226–239. https://doi.org/10.1016/j.fsigen.2016.05.007
- 4Bright JA, Richards R, Kruijver M, Kelly H, McGovern C, Magee A, et al. Internal validation of STRmix™ – a multi laboratory response to PCAST. Forensic Sci Int Genet. 2018; 34: 11–24. https://doi.org/10.1016/j.fsigen.2018.01.003
- 5 Scientific Working Group on DNA Analysis Methods. Guidelines for the validation of probabilistic genotyping systems. 2015. https://www.swgdam.org/_files/ugd/4344b0_22776006b67c4a32a5ffc04fe3b56515.pdf. Accessed 10 January 2024.
- 6Perlin MW, Legler MM, Spencer CE, Smith JL, Allan WP, Belrose JL, et al. Validating TrueAllele® DNA mixture interpretation. J Forensic Sci. 2011; 56(6): 1430–1447. https://doi.org/10.1111/j.1556-4029.2011.01859.x
- 7Perlin MW, Dormer K, Hornyak J, Schiermeier-Wood L, Greenspoon S. TrueAllele casework on Virginia DNA mixture evidence: computer and manual interpretation in 72 reported criminal cases. PLoS One. 2014; 9(3):e92837. https://doi.org/10.1371/journal.pone.0092837
- 8Buckleton JS, Bright JA, Gittelson S, Moretti TR, Onorato AJ, Bieber FR, et al. The probabilistic genotyping software STRmix: utility and evidence for its validity. J Forensic Sci. 2019; 64(2): 393–405. https://doi.org/10.1111/1556-4029.13898
- 9Perlin MW, Belrose JL, Duceman BW. New York state TrueAllele® casework validation study. J Forensic Sci. 2013; 58(6): 1458–1466. https://doi.org/10.1111/1556-4029.12223
- 10Greenspoon SA, Schiermeier-Wood L, Jenkins BC. Establishing the limits of TrueAllele® casework: a validation study. J Forensic Sci. 2015; 60(5): 1263–1276. https://doi.org/10.1111/1556-4029.12810
- 11Gill P, Benschop C, Buckleton J, Bleka Ø, Taylor D. A review of probabilistic genotyping systems: EuroForMix, DNAStatistX and STRmix™. Genes (Basel). 2021; 12(10):1559. https://doi.org/10.3390/genes12101559
- 12Perlin MW, Hornyak JM, Sugimoto G, Miller KW. TrueAllele® genotype identification on DNA mixtures containing up to five unknown contributors. J Forensic Sci. 2015; 60(4): 857–868. https://doi.org/10.1111/1556-4029.12788
- 13Bright 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. https://doi.org/10.1016/j.fsigen.2014.06.009
- 14Taylor D, Bright JA, Buckleton J. The interpretation of single source and mixed DNA profiles. Forensic Sci Int Genet. 2013; 7(5): 516–528. https://doi.org/10.1016/j.fsigen.2013.05.011
- 15Bright JA, Dukes MJ, Pugh SN, Evett IW, Buckleton JS. Applying calibration to LRs produced by a DNA interpretation software. Aust J Forensic Sci. 2021; 53(2): 147–153. https://doi.org/10.1080/00450618.2019.1682668
- 16Buckleton JS, Kruijver M, Curran JM, Bright J. Calibration of STRmix LRs following the method of Hannig et al. Auckland, New Zealand: Institute of Environmental Science and Research; 2020. https://research.esr.cri.nz/articles/report/Calibration_of_STRmix_LRs_following_the_method_of_Hannig_et_al_/12324011. Accessed 15 March 2024.
- 17Hannig J, Riman S, Iyer H, Vallone PM. Are reported likelihood ratios well calibrated? Forensic Sci Int Genet Suppl Ser. 2019; 7(1): 572–574. https://doi.org/10.1016/j.fsigss.2019.10.094
- 18Alladio E, Omedei M, Cisana S, D'Amico G, Caneparo D, Vincenti M, et al. DNA mixtures interpretation – a proof-of-concept multi-software comparison highlighting different probabilistic methods' performances on challenging samples. Forensic Sci Int Genet. 2018; 37: 143–150. https://doi.org/10.1016/j.fsigen.2018.08.002
- 19Barrio PA, Crespillo M, Luque JA, Aler M, Baeza-Richer C, Baldassarri L, et al. GHEP-ISFG collaborative exercise on mixture profiles (GHEP-MIX06). Reporting conclusions: results and evaluation. Forensic Sci Int Genet. 2018; 35: 156–163. https://doi.org/10.1016/j.fsigen.2018.05.005
- 20You Y, Balding D. A comparison of software for the evaluation of complex DNA profiles. Forensic Sci Int Genet. 2019; 40: 114–119. https://doi.org/10.1016/j.fsigen.2019.02.014
- 21Riman S, Iyer H, Vallone PM. Examining performance and likelihood ratios for two likelihood ratio systems using the PROVEDIt dataset. PLoS One. 2021; 16(9):e0256714. https://doi.org/10.1371/journal.pone
- 22Buckleton J, Bright JA, Taylor D, Wivell R, Bleka Ø, Gill P, et al. Examining performance and likelihood ratios for two likelihood ratio systems using the PROVEDIt dataset. Forensic Sci Int Genet. 2022; 59:102709. https://doi.org/10.1016/j.fsigen.2022.102709
- 23Cheng K, Bleka Ø, Gill P, Curran J, Bright JA, Taylor D, et al. A comparison of likelihood ratios obtained from EuroForMix and STRmix™. J Forensic Sci. 2021; 66(6): 2138–2155. https://doi.org/10.1111/1556-4029.14886
- 24 Laboratory for Forensic Technology Development & Integration. PROVEDIt database. https://lftdi.camden.rutgers.edu/provedit/files/. Accessed 9 April 2024.
- 25Butler 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. https://doi.org/10.1016/j.fsigen.2018.07.024
- 26Buckleton J, Susik M, Curran JM, Cheng K, Taylor D, Bright JA, et al. A diagnosis of the primary difference between EuroForMix and STRmix™. J Forensic Sci. 2024; 69(1): 40–51. https://doi.org/10.1111/1556-4029.15387
- 27Perlin MW. Efficient construction of match strength distributions for uncertain multi-locus genotypes. Heliyon. 2018; 4(10):e00824. https://doi.org/10.1016/j.heliyon.2018.e00824
- 28Perlin MW, Lancia G, Ng SK. Toward fully automated genotyping: genotyping microsatellite markers by deconvolution. Am J Hum Genet. 1995; 57(5): 1199–1210.
- 29 STRmix™ V2.6 User's manual. Wellington: Institute of Environmental Science and Research Ltd.; 2018.
- 30 People v Hillary NY DNA admissibility Ind. #:2015-15 (NY 2016).
- 31 People v William WI. Case No. 2020CF004062 (WI 2022).
- 32 Virginia Department of Forensic Science. Procedures manual, Extraction of DNA. https://www.dfs.virginia.gov/documentation-publications/manuals/. Accessed 10 January 2024.
- 33 Virginia Department of Forensic Science. Procedures manual, Plexor® HY quantitation of DNA. https://www.dfs.virginia.gov/documentation-publications/manuals/. Accessed 10 January 2024.
- 34 Promega. PowerQuant® System technical manual. 2020. https://www.promega.com/resources/protocols/technical-manuals/101/powerquant-system-protocol/. Accessed 30 March 2022.
- 35 Virginia Department of Forensic Science. Procedures manual, PowerPlex® fusion amplification and long term storage. https://www.dfs.virginia.gov/documentation-publications/manuals/. Accessed 10 January 2024.
- 36 Virginia Department of Forensic Science. Procedures manual, Analysis of CE results using GeneMapper® ID-X. https://www.dfs.virginia.gov/documentation-publications/manuals/. Accessed 10 January 2024.
- 37 Virginia Department of Forensic Science. Procedures manual, Interpretation of PowerPlex® Fusion CE Data. https://www.dfs.virginia.gov/documentation-publications/manuals/. Accessed 10 January 2024.
- 38 National Research Council (US). Committee on DNA forensic science: an update. The evaluation of forensic DNA evidence. Washington, DC: National Academies Press; 1996. p. 29–30.
- 39 Virginia Department of Forensic Science. Procedures manual, TrueAllele® Casework system. https://www.dfs.virginia.gov/documentation-publications/manuals/. Accessed 9 April 2024.
- 40 STRmix™ V2.6 operation manual. Wellington: Institute of Environmental Science and Research Ltd.; 2018.
- 41 STRmix™ V2.6 implementation and validation guide. Wellington: Institute of Environmental Science and Research Ltd.; 2018.
- 42Russell L, Cooper S, Wivell R, Kerr Z, Taylor D, Buckleton J, et al. A guide to results and diagnostics within a STRmix™ report. Wires Forensic Sci. 2019; 1(6): 1–12. https://doi.org/10.1002/wfr2.1354
10.1002/wfs2.1354 Google Scholar
- 43 Virginia Department of Forensic Science. Procedures manual, STRmix™ system. https://www.dfs.virginia.gov/documentation-publications/manuals/. Accessed 9 April 2024.
- 44 Idaho State Police Forensic Services. https://isp.idaho.gov/forensics/wp-content/uploads/sites/10/documents/currentAMs/BiologyDNA/Biology%20DNA%20Casework%20Methods%20Rev12.pdf. Accessed 17 April 2023.
- 45Schuerman C, Kalafut T, Buchanan C, Sutton J, Bright JA. Using the nondonor distribution to improve communication and inform decision making for low LRs from minor contributors in mixed DNA profiles. J Forensic Sci. 2020; 65(4): 1072–1084. https://doi.org/10.1111/1556-4029.14306
- 46Bright JA, Taylor D, Curran JM, Buckleton JS. Developing allelic and stutter peak height models for a continuous method of DNA interpretation. Forensic Sci Int Genet. 2013; 7(2): 296–304. https://doi.org/10.1016/j.fsigen.2012.11.013
- 47Greenspoon SA, Schiermeier-Wood L, Jenkins BC. Further exploration of TrueAllele® casework. Proceedings of the 26th International Symposium on Human Identification; 2015 Oct 12–15; Grapevine, TX. Madison, WI: Promega; 2015.
- 48Buckleton JS, Bright JA, Cheng K, Kelly H, Talyor DA. The effect of varying the number of contributors in the prosecution and alternate propositions. Forensic Sci Int Genet. 2019; 38: 225–231. https://doi.org/10.1016/j.fsigen.2018.11.011
- 49Perez J, Mitchell AA, Ducasse N, Tamariz J, Caragine T. 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. https://doi.org/10.3325/cmj.2011.52.314
- 50Haned H, Pène L, Lobry JR, Dufour AB, Pontier D. Estimating the number of contributors to forensic DNA mixtures: does maximum likelihood perform better than maximum allele count? J Forensic Sci. 2011; 56(1): 23–28. https://doi.org/10.1111/j.1556-4029.2010.01550.x
- 51Buckleton 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. https://doi.org/10.1016/j.fsigen.2006.09.002
- 52 Scientific Working Group on DNA Analysis Methods. Recommendations of the SWGDAM Ad Hoc Working Group on genotyping results reported as likelihood ratios. https://www.swgdam.org/_files/ugd/4344b0_dd5221694d1448588dcd0937738c9e46.pdf. Accessed 22 March 2023.
- 53Thompson W. Uncertainty in probabilistic genotyping of low template DNA: a case study comparing STRmix™ and TrueAllele®. J Forensic Sci. 2023; 68(3): 1049–1063. https://doi.org/10.1111/1556-4029.15225
- 54 Las Vegas Metropolitan Police Department. Forensic laboratory manuals. https://www.lvmpd.com/about/bureaus/forensic-laboratory/forensic-laboratory-manuals/-folder-59. Accessed 22 May 2024.
- 55 NYC Office of Chief Medical Examiner. Forensic biology manuals. https://www.nyc.gov/assets/ocme/downloads/pdf/technical-manuals/forensic-biology-technical-manuals/str_results_interpretaion_fusion_strmix_080522.pdf. Accessed 9 January 2024.
- 56 Virginia Department of Forensic Science. 210-D2016 FB PM interpretation of fusion data. https://dfs.virginia.gov/wp-content/uploads/210-D2016%20FB%20PM%20Interpretation%20of%20Fusion%20Data-4063-65a94f32d4888.pdf. Accessed 22 May 2024.