In traditional forensic DNA casework, the inclusion or exclusion of individuals who
may have contributed to an item of evidence may be dependent upon the assumption on
the number of individuals from which the evidence arose. Typically, the determination of
the minimum number of contributors (NOC) to a mixture is achieved by counting the
number of alleles observed above a given analytical threshold (AT); this technique is
known as maximum allele count (MAC). However, advances in polymerase chain reaction (PCR) chemistries and improvements in analytical sensitivities have led to an increase in the detection of complex, low template DNA (LtDNA) mixtures for which MAC is an inadequate means of determining the actual NOC. Despite the addition of highly polymorphic loci to multiplexed PCR kits and the advent of interpretation softwares which
deconvolve DNA mixtures, a gap remains in the DNA analysis pipeline, where an effective method of determining the NOC needs to be established.
The emergence of NOCIt -- a computational tool which provides the probability
distribution on the NOC, may serve as a promising alternative to traditional, threshold-
based methods. Utilizing user-provided calibration data consisting of single source samples of known genotype, NOCIt calculates the a posteriori probability (APP) that an evidentiary sample arose from 0 to 5 contributors. The software models baseline noise, reverse and forward stutter proportions, stutter and allele dropout rates, and allele heights. This information is then utilized to determine whether the evidentiary profile originated from one or many contributors. In short, NOCIt provides information not only on the likely NOC, but whether more than one value may be deemed probable. In the latter case, it may be necessary to modify downstream interpretation steps such that multiple values for the NOC are considered or the conclusion that most favors the defense is adopted.
Phase I of this study focused on establishing the minimum number of single source
samples needed to calibrate NOCIt. Once determined, the performance of NOCIt was
evaluated and compared to that of two other methods: the maximum likelihood estimator
(MLE) -- accessed via the forensim R package, and MAC. Fifty (50) single source samples proved to be sufficient to calibrate NOCIt, and results indicate NOCIt was the most accurate method of the three.
Phase II of this study explored the effects of template mass and sample complexity
on the accuracy of NOCIt. Data showed that the accuracy decreased as the NOC increased: for 1- and 5-contributor samples, the accuracy was 100% and 20%, respectively. The minimum template mass from any one contributor required to consistently estimate the true NOC was 0.07 ng -- the equivalent of approximately 10 cells' worth of DNA.
Phase III further explored NOCIt and was designed to assess its robustness.
Because the efficacy of determining the NOC may be affected by the PCR kit utilized, the
results obtained from NOCIt analysis of 1-, 2-, 3-, 4-, and 5-contributor mixtures amplified
with AmpFlstr® Identifiler® Plus and PowerPlex® 16 HS were compared. A positive
correlation was observed for all NOCIt outputs between kits. Additionally, NOCIt was
found to result in increased accuracies when analyzed with 1-, 3-, and 4-contributor
samples amplified with Identifiler® Plus and with 5-contributor samples amplified with PowerPlex® 16 HS. The accuracy rates obtained for 2-contributor samples were equivalent between kits; therefore, the effect of amplification kit type on the ability to determine the NOC was not substantive.
Cumulatively, the data indicate that NOCIt is an improvement to traditional methods
of determining the NOC and results in high accuracy rates with samples containing
sufficient quantities of DNA. Further, the results of investigations into the effect of
template mass on the ability to determine the NOC may serve as a caution that forensic
DNA samples containing low-target quantities may need to be interpreted using multiple
or different assumptions on the number of contributors, as the assumption on the number
of contributors is known to affect the conclusion in certain casework scenarios. As a
significant degree of inaccuracy was observed for all methods of determining the NOC at
severe low template amounts, the data presented also challenge the notion that any DNA sample can be utilized for comparison purposes. This suggests that the ability to detect extremely complex, LtDNA mixtures may not be commensurate with the ability to
accurately interpret such mixtures, despite critical advances in software-based analysis. In addition to the availability of advanced comparison algorithms, limitations on the
interpretability of complex, LtDNA mixtures may also be dependent on the amount of
biological material present on an evidentiary substrate.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/16179 |
| Date | 08 April 2016 |
| Creators | Alfonse, Lauren Elizabeth |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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