Allele sharing in first-degree and unrelated pairs of individuals in the Ge.F.I. AmpFlSTR® Profiler Plus™ database

Presciuttini, Silvano; Ciampini, Francesca; Alù, Milena; Cerri, N.; Dobosz, Marina; Domenici, Ranieri; Peloso, G.; Pelotti, Susi; Piccinini, A.; Ponzano, E.; Ricci, U.; Tagliabracci, Adriano; Baley-Wilson, J.E; Stefano, Francesco De; Pascali, Vincenzo Lorenzo

doi:10.1016/s0379-0738(02)00399-7

Cited by 23 publications

(11 citation statements)

References 11 publications

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“…compared are related to each other. Simulations confirm that firstdegree relatives (siblings) are more likely to have alleles in common than second degree relatives (cousins) or unrelated individuals (13) (Fig. 3).…”

Section: Discussionmentioning

confidence: 65%

Empirical Analysis of the STR Profiles Resulting from Conceptual Mixtures

Paoletti

Doom

Krane

et al. 2005

Journal of Forensic Sciences

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Samples containing DNA from two or more individuals can be difficult to interpret. Even ascertaining the number of contributors can be challenging and associated uncertainties can have dramatic effects on the interpretation of testing results. Using an FBI genotypes dataset, containing complete genotype information from the 13 Combined DNA Index System (CODIS) loci for 959 individuals, all possible mixtures of three individuals were exhaustively and empirically computed. Allele sharing between pairs of individuals in the original dataset, a randomized dataset and datasets of generated cousins and siblings was evaluated as were the number of loci that were necessary to reliably deduce the number of contributors present in simulated mixtures of four or less contributors. The relatively small number of alleles detectable at most CODIS loci and the fact that some alleles are likely to be shared between individuals within a population can make the maximum number of different alleles observed at any tested loci an unreliable indicator of the maximum number of contributors to a mixed DNA sample. This analysis does not use other data available from the electropherograms (such as peak height or peak area) to estimate the number of contributors to each mixture. As a result, the study represents a worst case analysis of mixture characterization. Within this dataset, approximately 3% of three-person mixtures would be mischaracterized as two-person mixtures and more than 70% of four-person mixtures would be mischaracterized as two-or three-person mixtures using only the maximum number of alleles observed at any tested locus.

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Section: Discussionmentioning

confidence: 65%

Empirical Analysis of the STR Profiles Resulting from Conceptual Mixtures

Paoletti

Doom

Krane

et al. 2005

Journal of Forensic Sciences

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“…This is supported by more detailed proficiency test reports that specified manual allele calling errors, lacking separators between the two alleles at one locus, exchange of alleles between loci [ 75 ] and the tendency toward the concentration of errors in some “not so good” submissions [ 22 , 33 , 61 , 64 , 65 , 75 ]. Further analyses on (published) datasets confirmed the role of transcriptional errors [ 22 ] and found duplicate genotypes across database subsets [ 21 , 22 , 78 ], locus name misspelling [ 34 ], as well as allele swapping [ 26 ]. Information on errors and error rates in MPS STR typing is expected from ongoing collaborative exercises (P.A.…”

Section: Discussionmentioning

confidence: 98%

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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“…Considering real markers, we selected for analysis the following four STRs, which are located in different linkage groups 23 and cover a wide range of allele number and heterozygosities (8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) distributions were obtained from publications by Toni and coworkers 17 and Bini and coworkers. 24 Because development and validation of X-STR are still growing, these markers have been chosen only as a useful example, and they could not be the best X-STR to use; for example, a recently developed commercial kit (Biotype AG, Dresden, Germany) includes the four loci DXS8378, DXS7132, HPRTB, and DXS7423.…”

Section: Comparing Relative Efficiencies Of X-strs and A-strsmentioning

confidence: 99%

“…Immigration policies encourage impersonation of parent and child bytwo other blood relatives, and in these cases not only parent‐child calculations, but also statistical tests for other possible relatedness are required (such as uncle‐child or full or half‐sibs). Other examples involving testing relationships between pairs of individuals include the attribution to missing individuals of one or more body remains, 6 identification of the victims of mass disasters, 7 validation of large databases of individual genetic profiles, 8,9 reconstruction of genealogies when there are no civic records, 10 or inferring relationships in ancient cemeteries 11 . When only duos must be evaluated, the power of a given set of genetic markers to provide evidence of a pretended true relationship is greatly reduced 12 and it is likely that the set of markers available in commercial kits does not provide statistical power to resolve relationships with sufficient confidence 13,14 …”

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confidence: 99%