GHEP-ISFG collaborative exercise on mixture profiles of autosomal STRs (GHEP-MIX01, GHEP-MIX02 and GHEP-MIX03): Results and evaluation

Crespillo, Manuel; Barrio, Pedro A.; Luque, J. A.; Alves, Cı́ntia; Aler, M.; Alessandrini, Federica; Andrade, L.; Barretto, R.M.; Bofarull, A.; Costa, Sandra; García, Martín; Garcı́a, Oscar; Gaviria, A.; Gladys, A.; Gorostiza, Amaya; Hernández, Alexis; Herrera, Miguel R. Paredes; Hombreiro, L.; Ibarra, A.; Jiménez, M.J.; Luque, G.M.; Madero, P.; Martı́nez-Jarreta, Begoña; Masciovecchio, M. V.; Modesti, Nidia M.; Moreno, Flavio Estrada; Pagano, S.; Pedrosa, Susana; Plaza, G.; Prat, Esther; Puente, Jorge; Rendo, Fernando; Ribeiro, Teresa; Sala, A.; Santamaria, Edwin; Saragoni, Victor G.; Whittle, M.R.

doi:10.1016/j.fsigen.2014.01.009

Cited by 14 publications

(6 citation statements)

References 17 publications

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“…Both inter-and intra-laboratory studies involve the distribution of mixtures with known ground truth, usually as electronic files after analysis, among forensic scientists within a laboratory and/or to a number of different laboratories. The compiled results give a measure of the variability in performance within and between laboratories [28][29][30][31][32][33][34][35][36][37]. At least two studies [38,39] (hereafter the GHEP-ISFG study and NIST studies) have appeared in courtroom discussion due to the wide range of results observed.…”

Section: Inter and Intra-laboratory Studiesmentioning

confidence: 99%

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

Gill

Benschop

Buckleton

et al. 2021

Genes

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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.

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Section: Inter and Intra-laboratory Studiesmentioning

confidence: 99%

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

Gill

Benschop

Buckleton

et al. 2021

Genes

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“…Crespillo et al [12] 32 (32) Prieto et al [13] 18 (20); 18 (22) 2 Data (csv format) provided for 16 STR loci with case scenarios; two exercises each involving a two-person mixture were supplied along with victim and suspect profiles, population allele frequencies, and LRmix software to explore impact of training and whether standardization of an approach could be demonstrated UK Forensic Science Regulator (2014) Unpublished report 8 (18) 5 DNA extracts provided with case scenarios for 2 two-person mixtures (4:1, 2:1) and 3 three-person mixtures (6:4:1, 6:3:1, 7:1.5:1) to explore variability across UK forensic science providers DFSC Mixture Study (2014-2015)…”

Section: Introductionmentioning

confidence: 99%

“…About a dozen interlaboratory studies exploring DNA mixture interpretation with short tandem repeat (STR) markers have been performed over the past two decades [8][9][10][11][12][13][14][15][16][17][18] Duewer et al [9] 22 (37)…”

Section: Introductionmentioning

confidence: 99%

NIST interlaboratory studies involving DNA mixtures (MIX05 and MIX13): Variation observed and lessons learned

Butler

Kline

Coble

2018

Forensic Science International: Genetics

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Interlaboratory studies are a type of collaborative exercise in which many laboratories are presented with the same set of data to interpret, and the results they produce are examined to get a "big picture" view of the effectiveness and accuracy of analytical protocols used across participating laboratories. In 2005 and again in 2013, the Applied Genetics Group of the National Institute of Standards and Technology (NIST) conducted interlaboratory studies involving DNA mixture interpretation. In the 2005 NIST MIX05 study, 69 laboratories interpreted data in the form of electropherograms of two-person DNA mixtures representing four different mock sexual assault cases with different contributor ratios. In the 2013 NIST MIX13 study,108 laboratories interpreted electropherogram data for five different case scenarios involving two, three, or four contributors, with some of the contributors potentially related. This paper describes the design of these studies, the variations observed among laboratory results, and lessons learned.

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“…The stated magnitude of errors or discordance in autosomal STR results rarely exceeded 1%, with a maximum of 4%, both in mock casework trials and kinship exercises, e.g., [ 33 , 46 , 54 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 ]. Higher error rates in mixture studies including low-template components [ 74 , 75 ] were not considered. Regardless of the method used in testing, human clerical errors in transcription of results were persistently reported, e.g., [ 21 , 33 , 46 , 48 , 54 , 64 , 66 , 69 , 74 , 75 , 76 , 77 ].…”

Section: Discussionmentioning

confidence: 99%

“…Higher error rates in mixture studies including low-template components [ 74 , 75 ] were not considered. Regardless of the method used in testing, human clerical errors in transcription of results were persistently reported, e.g., [ 21 , 33 , 46 , 48 , 54 , 64 , 66 , 69 , 74 , 75 , 76 , 77 ]. While most authors did not detail the type of human error, a broad spectrum mirrored by the STRidER QC can be expected.…”

Section: Discussionmentioning

confidence: 99%

The STRidER Report on Two Years of Quality Control of Autosomal STR Population Datasets

Bodner

Parson

2020

Genes

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STRidER, the STRs for Identity ENFSI Reference Database, is a curated, freely publicly available online allele frequency database, quality control (QC) and software platform for autosomal Short Tandem Repeats (STRs) developed under the endorsement of the International Society for Forensic Genetics. Continuous updates comprise additional STR loci and populations in the frequency database and many further STR-related aspects. One significant innovation is the autosomal STR data QC provided prior to publication of datasets. Such scrutiny was lacking previously, leaving QC to authors, reviewers and editors, which led to an unacceptably high error rate in scientific papers. The results from scrutinizing 184 STR datasets containing >177,000 individual genotypes submitted in the first two years of STRidER QC since 2017 revealed that about two-thirds of the STR datasets were either being withdrawn by the authors after initial feedback or rejected based on a conservative error rate. Almost no error-free submissions were received, which clearly shows that centralized QC and data curation are essential to maintain the high-quality standard required in forensic genetics. While many errors had minor impact on the resulting allele frequencies, multiple error categories were commonly found within single datasets. Several datasets contained serious flaws. We discuss the factors that caused the errors to draw the attention to redundant pitfalls and thus contribute to better quality of autosomal STR datasets and allele frequency reports.

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GHEP-ISFG collaborative exercise on mixture profiles of autosomal STRs (GHEP-MIX01, GHEP-MIX02 and GHEP-MIX03): Results and evaluation

Cited by 14 publications

References 17 publications

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

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

NIST interlaboratory studies involving DNA mixtures (MIX05 and MIX13): Variation observed and lessons learned

The STRidER Report on Two Years of Quality Control of Autosomal STR Population Datasets

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