Run‐Specific Limits of Detection and Quantitation for STR‐based DNA Testing

Abstract

STR-based DNA profiling is an exceptionally sensitive analytical technique that is often used to obtain results at the very limits of its sensitivity. The challenge of reliably distinguishing between signal and noise in such situations is one that has been rigorously addressed in numerous other analytical disciplines. However, an inability to determine accurately the height of electropherogram baselines has caused forensic DNA profiling laboratories to utilize alternative approaches. Minimum thresholds established during laboratory validation studies have become the de facto standard for distinguishing between reliable signal and noise/technical artifacts. These minimum peak height thresholds generally fail to consider variability in the sensitivity of instruments, reagents, and the skill of human analysts involved in the DNA profiling process over the course of time. Software (BatchExtract) made publicly available by the National Center for Biotechnology Information now provides an alternative means of establishing limits of detection and quantitation that is more consistent with those used in other analytical disciplines. We have used that software to determine the height of each data collection point for each dye along a control sample's electropherogram trace. These values were then used to determine a limit of detection (the average amount of background noise plus three standard deviations) and a limit of quantitation (the average amount of background noise plus 10 standard deviations) for each control sample. Analyses of the electropherogram data associated with the positive, negative, and reagent blank controls included in 50 different capillary electrophoresis runs validate that this approach could be used to determine run-specific thresholds objectively for use in forensic DNA casework.

Comprehensive One-Step Molecular Analyses of Mitochondrial Genome by Massively Parallel Sequencing

“…2A). Thus, the limit of detection, calculated as 3 SDs above the mean error (0.326 ϩ 3 ϫ 0.335), was 1.33% under our current experimental, instrumental, and analytic conditions (22,23 ). It is worth noting that the experimental procedures can introduce errors, which, in general, are higher for mtDNA samples than for the ExQC control, as shown in Fig.…”

Probabilistic characterisation of baseline noise in STR profiles

“…Determination of the AT via the following approach has been described in both the forensic and analytical chemistry literature [6,18,[29][30][31][32] based on a Gaussian noise assumption. One estimates the mean m and standard deviation s of the non-zero noise observations, circa 50 per profile in our data, picks a number of standard deviations k, and sets…”

“…The fact that the conservative nature of analytical thresholds has been criticised led [18] to analyse the baseline noise. Information loss may be kept low by applying an optimal analytical threshold that suppresses most of the noise while enhancing the detection of alleles [6].…”

“…Noise in STR profiles is commonly modelled via Gaussian distributions [18,17], though log-normal distributions have also been suggested [6]. In [17], a Gaussian noise model is used for determining the likelihood that a given number of individuals contributed to a mixed sample.…”

Avoiding Errors and Pitfalls in Evidence Sampling for Forensic Genetics

“…The background noise is generally eliminated by the establishing a threshold of 50 RFU. In order to avoid false homozygote by allelic drop-out , separate thresholds were established referred to as the low-template DNA threshold T, the match interpretation threshold , the limit of quantitation (Gilder et al, 2007) is set at 150-200 RFU. The allele peaks should be above this limit to be sure that it is a true homozygous but even the respect of this limit may not prevent allele drop-out in all cases.…”