The interpretation of mixed DNA profiles from a mother, father, and child trio

Lin, Ming-Huei; Bright, Jo‐Anne; Pugh, Simone N.; Buckleton, John

doi:10.1016/j.fsigen.2019.102175

Cited by 10 publications

(10 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Reference Ability of STRmix™ to deconvolute profiles and assign LRs that comport to manual interpretation and human expectation [15] Ability of STRmix™ to discriminate between donors and non-donors in database searches [190] Behaviour of STRmix™ to assign LRs when dealing with multiple replicates, different number of contributors, and assumed contributors [163] Sensitivity of LR produced by STRmix™ to different factors of uncertainty such as theta, relatedness of alternate DNA source and length of MCMC analysis [171] Tests to be performed when validating probabilistic genotyping, using STRmix™ as an example [112] Ability of individuals from different laboratories to standardise evaluations when using STRmix™ [33,53] Ability of STRmix™ to reliably use peak height information in very low intensity profiles [56,132,210] Ability of STRmix™ to discriminate between donors and non-donors in large-scale Hd true tests, or using importance sampling [59,60,190,200,21 2,213] Sensitivity of STRmix™ model parameters to laboratory factors [196,198] Ability of STRmix™ to utilise information from profiles produced under different laboratory conditions within a single analysis [155] Effect of mixture complexity, allele sharing and contributor proportions on the ability STRmix™ to distinguish contributors from non-contributors [54] The ability of STRmix™ to identify common DNA donors in mixed samples [25,159] The sensitivity of LRs produced in STRmix™ to the choice of the number of contributors [71,72,97] Ability to use STRmix™ to resolve major components of mixtures [72] Testing the assumption of additivity of peak heights in STRmix™ models [159,160] Performance of the degradation model within STRmix™ [214] The effect of relatedness of contributors to the STRmix™ analysis [203,215] Testing the calibration of LRs produced in STRmix™ [58] Validation overviews of STRmix™ [205,216] Comparison of STRmix™ ...…”

Section: Focus Of Validationmentioning

confidence: 99%

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Gill

Benschop

Buckleton

et al. 2021

Genes

View full text Add to dashboard Cite

Probabilistic genotyping has become widespread. EuroForMix and DNAStatistX are both based upon maximum likelihood estimation using a γ model, whereas STRmix™ is a Bayesian approach that specifies prior distributions on the unknown model parameters. A general overview is provided of the historical development of probabilistic genotyping. Some general principles of interpretation are described, including: the application to investigative vs. evaluative reporting; detection of contamination events; inter and intra laboratory studies; numbers of contributors; proposition setting and validation of software and its performance. This is followed by details of the evolution, utility, practice and adoption of the software discussed.

show abstract

Section: Focus Of Validationmentioning

confidence: 99%

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Gill

Benschop

Buckleton

et al. 2021

Genes

View full text Add to dashboard Cite

show abstract

“…But even with D = 0.2 and e = 0.01, the consensus accuracies of all contributors approach 100% for mixtures with ≥40 cells and relatively balanced mixture ratios. Particularly, the family trio mixtures can be deconvoluted to recover the genotypes of the individual contributors, even though related, which in theory is more challenging with CE-STR analysis without conditioning on one of the contributors [65]. This study did not investigate the consensus accuracies when the estimated NOC was incorrect.…”

Section: The Capabilities and Limitationsmentioning

confidence: 99%

Precision DNA Mixture Interpretation with Single-Cell Profiling

King

Smuts

et al. 2021

Genes

View full text Add to dashboard Cite

Wet-lab based studies have exploited emerging single-cell technologies to address the challenges of interpreting forensic mixture evidence. However, little effort has been dedicated to developing a systematic approach to interpreting the single-cell profiles derived from the mixtures. This study is the first attempt to develop a comprehensive interpretation workflow in which single-cell profiles from mixtures are interpreted individually and holistically. In this approach, the genotypes from each cell are assessed, the number of contributors (NOC) of the single-cell profiles is estimated, followed by developing a consensus profile of each contributor, and finally the consensus profile(s) can be used for a DNA database search or comparing with known profiles to determine their potential sources. The potential of this single-cell interpretation workflow was assessed by simulation with various mixture scenarios and empirical allele drop-out and drop-in rates, the accuracies of estimating the NOC, the accuracies of recovering the true alleles by consensus, and the capabilities of deconvolving mixtures with related contributors. The results support that the single-cell based mixture interpretation can provide a precision that cannot beachieved with current standard CE-STR analyses. A new paradigm for mixture interpretation is available to enhance the interpretation of forensic genetic casework.

show abstract

“…Conditioning has previously been shown to be highly valuable for all mixtures, especially those with high allelic overlap [5,7,10,11] such as mixtures of close relatives.…”

Section: We Use Different Sets Of Propositions Which Lead To Differentmentioning

confidence: 99%

“…Conditioning is sufficiently beneficial that it should be undertaken whenever reasonable [5,7,10], as it is a powerful tool in avoiding adventitious inclusions. This can, and should be done, even if there is no specific proposition aligning with a conditioned LR, as the court might find value in knowing that two POI cannot be included in a mixture together.…”

Section: Considering An Exhaustive Set Of Propositions By Conditionin...mentioning

confidence: 99%

A mixed DNA profile controversy revisited

Kalafut

Pugh²,

Gill

et al. 2021

Journal of Forensic Sciences

View full text Add to dashboard Cite

Semaan et al. (J Forensic Res, 2020, 11, 453) discuss a mock case “where eight different individuals [P1 through P8] could not be excluded in a mixed DNA analysis. Even though … expert DNA mixture analysis software was used.” Two of these are the true donors. The LRs reported are incorrect due to the incorrect entry of propositions into LRmix Studio. This forced the software to account for most of the alleles as drop‐in, resulting in LRs 60–70 orders of magnitude larger than expected. P1, P2, P4, P5, and P8 can be manually excluded using peak heights. This has relevance when using LRmix which does not use peak heights. We extend the work using the same two reference genotypes who were the true contributors as Semaan et al. (J Forensic Res, 2020, 11, 453). We simulate three two‐donor mixtures with peak heights using these two genotypes and analyze using STRmix™. For the simulated 1:1 mixture, one of the non‐donors’ LRs supported him being a contributor when no conditioning was used. When considered in combination with any other potential donors (i.e., with conditioning), this non‐donor was correctly eliminated. For the 3:1 mixture, all results correctly supported that the non‐donors were not contributors. The low‐template 4:1 mixture LRs with no conditioning showed support for all eight profiles as donors. However, the results from pair‐wise conditioning showed that only the two ground truth donors had LRs supporting that they were contributors to the mixture. We recommend the use of peak heights and conditioning profiles, as this allows better sensitivity and specificity even when the persons share many alleles.

show abstract

The interpretation of mixed DNA profiles from a mother, father, and child trio

Cited by 10 publications

References 19 publications

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Precision DNA Mixture Interpretation with Single-Cell Profiling

A mixed DNA profile controversy revisited

Contact Info

Product

Resources

About