Probabilistic characterisation of baseline noise in STR profiles

Monich, Ulrich J.; Duffy, Ken R.; Médard, Muriel; Cadambe, Viveck R.; Alfonse, Lauren E.; Grgicak, Catherine M.

doi:10.1016/j.fsigen.2015.07.001

Cited by 22 publications

(19 citation statements)

References 26 publications

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“…Noise is an inherent instrument issue that, according to a recent study , occurs at approximately 15% of allelic positions, and when it occurs is best described as a log‐normal distribution. Log‐normal distributions are more prone to large outliers than normal distributions and can generate noise that is of similar peak height to true and stutter products in the presence of low starting template or less numerous rounds of PCR, N PCR .…”

Section: Methodsmentioning

confidence: 99%

“…Log‐normal distributions are more prone to large outliers than normal distributions and can generate noise that is of similar peak height to true and stutter products in the presence of low starting template or less numerous rounds of PCR, N PCR . For the model, we incorporate the finding by independently adding noise at each allelic position with probability 0.15, whereupon it follows a log‐normal with a per‐locus mean, μ noise , and variance,

σ_{noise}^{2}

, taken from . If noise occurs at a position assigned to true or stuttered alleles, its fluorescence is treated as additive.…”

Section: Methodsmentioning

confidence: 99%

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Exploring STR signal in the single‐ and multicopy number regimes: Deductions from an in silico model of the entire DNA laboratory process

et al. 2017

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Short tandem repeat (STR) profiling from DNA samples has long been the bedrock of human identification. The laboratory process is composed of multiple procedures that include quantification, sample dilution, PCR, electrophoresis, and fragment analysis. The end product is a short tandem repeat electropherogram comprised of signal from allele, artifacts, and instrument noise. In order to optimize or alter laboratory protocols, a large number of validation samples must be created at significant expense. As a tool to support that process and to enable the exploration of complex scenarios without costly sample creation, a mechanistic stochastic model that incorporates each of the aforementioned processing features is described herein. The model allows rapid in silico simulation of electropherograms from multicontributor samples and enables detailed investigations of involved scenarios. An implementation of the model that is parameterized by extensive laboratory data is publically available. To illustrate its utility, the model was employed in order to evaluate the effects of sample dilutions, injection time, and cycle number on peak height, and the nature of stutter ratios at low template. We verify the model's findings by comparison with experimentally generated data.

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Section: Methodsmentioning

confidence: 99%

σ_{noise}^{2}

, taken from . If noise occurs at a position assigned to true or stuttered alleles, its fluorescence is treated as additive.…”

Section: Methodsmentioning

confidence: 99%

Exploring STR signal in the single‐ and multicopy number regimes: Deductions from an in silico model of the entire DNA laboratory process

et al. 2017

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“…34 Characterization of reproducible artefacts, such as polymer specific arte-35 facts, is an important part of developmental validations of new STR multiplex 36 kits [25,26]. Although not specifically mentioned in the recommended min- 37 imum criteria for validation [1] it useful to know the type and magnitude of 38 artefacts produced under the specific conditions in the laboratory. 39 Here we present a practical approach to monitor and characterize artefacts 40 and contamination using negative controls.…”

mentioning

confidence: 99%

“…The baseline noise was best described by a log-normal 135 distribution (data not shown). Therefore, the AT was estimated according 136 to the formula in Mönich et al[38] reproduced below:…”

mentioning

confidence: 99%

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Characterisation of artefacts and drop-in events using STR-validator and single-cell analysis

Hansson

Gill

2017

Forensic Science International: Genetics

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Towards developing forensically relevant single-cell pipelines by incorporating direct-to-PCR extraction: compatibility, signal quality, and allele detection

et al. 2021

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Current analysis of forensic DNA stains relies on the probabilistic interpretation of bulk-processed samples that represent mixed profiles consisting of an unknown number of potentially partial representations of each contributor. Single-cell methods, in contrast, offer a solution to the forensic DNA mixture problem by incorporating a step that separates cells before extraction. A forensically relevant single-cell pipeline relies on efficient direct-to-PCR extractions that are compatible with standard downstream forensic reagents. Here we demonstrate the feasibility of implementing single-cell pipelines into the forensic process by exploring four metrics of electropherogram (EPG) signal quality-i.e., allele detection rates, peak heights, peak height ratios, and peak height balance across low-to high-molecular-weight short tandem repeat (STR) markers-obtained with four direct-to-PCR extraction treatments and a common post-PCR laboratory procedure. Each treatment was used to extract DNA from 102 single buccal cells, whereupon the amplification reagents were immediately added to the tube and the DNA was amplified/injected using post-PCR conditions known to elicit a limit of detection (LoD) of one DNA molecule. The results show that most cells, regardless of extraction treatment, rendered EPGs with at least a 50% true positive allele detection rate and that allele drop-out was not cell independent. Statistical tests demonstrated that extraction treatments significantly impacted all metrics of EPG quality, where the Arcturus® PicoPure™ extraction method resulted in the lowest median allele drop-out rate, highest median average peak height, highest median average peak height ratio, and least negative median values of EPG sloping for GlobalFiler™ STR loci amplified at half volume. We, therefore, conclude the feasibility of implementing single-cell pipelines for casework purposes and demonstrate that inferential systems assuming cell independence will not be appropriate in the probabilistic interpretation of a collection of single-cell EPGs.

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Probabilistic characterisation of baseline noise in STR profiles

Cited by 22 publications

References 26 publications

Exploring STR signal in the single‐ and multicopy number regimes: Deductions from an in silico model of the entire DNA laboratory process

Exploring STR signal in the single‐ and multicopy number regimes: Deductions from an in silico model of the entire DNA laboratory process

Characterisation of artefacts and drop-in events using STR-validator and single-cell analysis

Towards developing forensically relevant single-cell pipelines by incorporating direct-to-PCR extraction: compatibility, signal quality, and allele detection

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