Grigora<scp>SNP</scp>s: Optimized Analysis of <scp>SNP</scp>s for <scp>DNA</scp> Forensics,

Ricke, Darrell O.; Shcherbina, Anna; Michaleas, Adam; Fremont-Smith, Philip

doi:10.1111/1556-4029.13794

Cited by 6 publications

(4 citation statements)

References 15 publications

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“…CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted February 8, 2021. ; https://doi.org/10.1101/2021.02.08.430218 doi: bioRxiv preprint when the number of SNPs placed at a forensic protocol is counted in hundreds [17][18][19][20] or possibly thousands [ 16,30,34]).…”

Section: Semi-continuous Calculationsmentioning

confidence: 99%

“…If used for semi-continuous calculations, matrices will only contain genotype frequencies, so that using the universal matrix for the n th SNP is only a matter of updating the worksheet's pair of gene frequencies with those of the locus of interest. Universal matrices become convenient to use when the number of SNPs placed at a forensic protocol is counted in hundreds [17][18][19][20] or possibly thousands [ 16,30,34]).…”

Section: Semi-continuous Calculationsmentioning

confidence: 99%

“…In view of this favourable background [2 ], several SNPs panels have been assembled for human identification and validated for the forensic routine [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] .…”

Section: Introductionmentioning

confidence: 99%

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Calculating likelihoods and likelihood ratios at SNPs-based mixtures. A reappraisal of the binomial inference, as applied to forensic identity tests

2021

Preprint

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Single nucleotide polymorphisms (SNPs) are useful forensic markers. When a SNPs-based forensic protocol targets a body fluid stain, it returns elementary evidence regardless of the number of individuals that might have contributed to the stain deposition. Therefore, drawing inference from a mixed stain with SNPs is different than drawing it while using multinomial polymorphisms. We here revisit this subject, with a view to contribute to a fresher insight into it. First, we manage to model conditional semi-continuous likelihoods in terms of matrices of genotype permutations vs number of contributors (NTZsc). Secondly, we redefine some algebraic formulas to approach the semi-continuous calculation. To address allelic dropouts, we introduce a peak height ratio index (‘h’, or: the minor read divided by the major read at any NGS-based typing result) into the semi-continuous formulas, for they to act as an acceptable proxy of the ‘split drop’ (Haned et al, 2012) model of calculation. Secondly, we introduce a new, empirical method to deduct the expected quantitative ratio at which the contributors of a mixture have originally mixed and the observed ratio generated by each genotype combination at each locus. Compliance between observed and expected quantity ratios is measured in terms of (1-χ2 ) values at each state of a locus deconvolution. These probability values are multiplied, along with the h index, to the relevant population probabilities to weigh the overall plausibility of each combination according to the quantitative perspective. We compare calculation performances of our empirical procedure (NITZq) with those of the EUROFORMIX software ver. 3.0.3. NITZq generates LR values a few orders of magnitude lower than EUROFORMIX when true contributors are used as POIs, but much lower LR values when false contributors are used as POIs. NITZ calculation routines may be useful, especially in combination with mass genomics typing protocols.

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Section: Semi-continuous Calculationsmentioning

confidence: 99%

Section: Semi-continuous Calculationsmentioning

confidence: 99%

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Calculating likelihoods and likelihood ratios at SNPs-based mixtures. A reappraisal of the binomial inference, as applied to forensic identity tests

2021

Preprint

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“…SNPs are practically ubiquitous; they can be typed en masse and their current typing procedures (next-generation sequencing; NGS) are unaffected by technical artifacts that normally complicate the process of STR typing [1][2]. Finally, several SNP panels have been assembled for human identification and validated for forensic routine [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

A novel computational strategy to predict the value of the evidence in the SNP-based forensic mixtures

Pascali

2021

PLoS ONE

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This study introduces a methodology for inferring the weight of the evidence (WoE) in the single nucleotide polymorphism (SNP)-typed DNA mixtures of forensic interest. First, we redefined some algebraic formulae to approach the semi-continuous calculation of likelihoods and likelihood ratios (LRs). To address the allelic dropouts, a peak height ratio index (“h,” an index of heterozygous state plausibility) was incorporated into semi-continuous formulae to act as a proxy for the “split-drop” model of calculation. Second, the original ratio at which a person of interest (POI) has entered into the mixture was inferred by evaluating the DNA amounts conferred by unique genotypes to any possible permutation of any locus of the typing protocol (unique genotypes are genotypes that appear just once in the relevant permutation). We compared this expected ratio (MRex) to all the mixing ratios emerging at all other permutations of the mixture (MRobs) using several (1 - χ2) tests to evaluate the probability of each permutation to exist in the mixture according to quantitative criteria. At the level of each permutation state, we multiplied the (1 - χ2) value to the genotype frequencies and the h index. All the products of all the permutation states were finally summed to give a likelihood value that accounts for three independent properties of the mixtures. Owing to the (1 - χ2) index and the h index, this approach qualifies as a fully continuous methodology of LR calculation. We compared the MRs and LRs emerging from our methodology to those generated by the EuroForMix software ver. 3.0.3. When the true contributors were tested as POIs, our procedure generated highly discriminant LRs that, unlike EuroForMix, never overcame the corresponding single-source LRs. When false contributors were tested as POIs, we obtained a much lower LR value than that from EuroForMix. These two findings indicate that our computational method is more reliable and realistic than EuroForMix.

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Analysis of complex DNA mixtures using massively parallel sequencing of SNPs with low minor allele frequencies

Petrovick

Boettcher

Fremont-Smith

et al. 2020

Forensic Science International: Genetics

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GrigoraSNPs: Optimized Analysis of SNPs for DNA Forensics,

Cited by 6 publications

References 15 publications

Calculating likelihoods and likelihood ratios at SNPs-based mixtures. A reappraisal of the binomial inference, as applied to forensic identity tests

Calculating likelihoods and likelihood ratios at SNPs-based mixtures. A reappraisal of the binomial inference, as applied to forensic identity tests

A novel computational strategy to predict the value of the evidence in the SNP-based forensic mixtures

Analysis of complex DNA mixtures using massively parallel sequencing of SNPs with low minor allele frequencies

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