Towards Commercialization: Preliminary Developmental Validation of a High Resolution Melt Curve Mixture Prediction Assay and SVM Tool, Virginia, 2020-2022 (ICPSR 39133)

Version Date: Aug 28, 2024

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Principal Investigator(s):
Tracey Dawson Cruz, Virginia Commonwealth University; Sarah J. Seashols-Williams, Virginia Commonwealth University; Edward L. Boone, Virginia Commonwealth University

https://doi.org/10.3886/ICPSR39133.v1

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Summary

In the current study, roughly 170 single source samples and 32 two-person mixture samples were tested using both the integrated Quantiplex®-high resolution melt (HRM) assay and Quantifiler™ Trio-HRM assay, then the entire HRM datasets were exported for prediction modeling using both linear discriminate analysis (LDA) and support vector machine (SVM) algorithms in R Studio software. For proof-of-concept, only 8 different genotypes, including a genotype of "mixture", were represented (for each locus) in testing. A portion of the samples tested were used to "train" the software and the remaining sample data was used as unknowns (or "validation") samples for prediction. When samples were tested in the Quantiplex®-HRM assay, an overall accuracy of 87.88 percent was exhibited, correctly classifying 87.5 percent of single source samples as such and 90 percent of mixture samples. Similarly, when samples were tested in the Quantifiler™ Trio-HRM assay an overall accuracy of 79.2 percent was exhibited, with 89.2 percent of single source samples accurately classifying and 43.8 percent of mixtures accurately classifying. Additionally, quantification values obtained from the integrated assays as well as the quality metrics such as the slope, R2, and y-intercept, were not significantly different than those obtained in the standard assays.

Citation

Dawson Cruz, Tracey, Seashols-Williams, Sarah J., and Boone, Edward L. Towards Commercialization: Preliminary Developmental Validation of a High Resolution Melt Curve Mixture Prediction Assay and SVM Tool, Virginia, 2020-2022. Inter-university Consortium for Political and Social Research [distributor], 2024-08-28. https://doi.org/10.3886/ICPSR39133.v1

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Funding

United States Department of Justice. Office of Justice Programs. National Institute of Justice (2019-DU-BX-0003)

Subject Terms

Geographic Coverage

Distributor(s)

Inter-university Consortium for Political and Social Research
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Time Period(s)

2020 -- 2022

Date of Collection

2020 -- 2022

Data Collection Notes

  1. These data are a Fast Track Release and are distributed as they were received from the data producer. Data files have been zipped for release, but not checked or processed. Users should refer to the accompanying ICPSR README file and P.I. documentation for information on the data available with this collection. Please consult with the investigator(s) if further information is needed.

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Study Purpose

Deconvolution of mixed genetic profiles can be challenging for even the most experienced forensic DNA examiners, particularly when only a few cells are present (such as with touch DNA samples). These low-level DNA samples often have high failure rates - showing data below established thresholds or showing complex mixtures, both of which present extreme interpretational challenges. Unfortunately, in the current workflow of forensic laboratories, both allele designation and mixture detection occur at the final step of the analytical process (data review). The late revelation of these issues proves problematic, as initial testing of touch DNA evidence samples often include consumption of the DNA. If screening tools could be developed to provide information about the number of contributors in the DNA sample earlier on in the DNA workflow, examiners could easily adjust amplification conditions or combine multiple swabs from the same item in an effort to improve the chances of generating a clear profile from the first round of testing, reducing the retest rate associated with the processing of touch DNA samples. A previous 2015 National Institute of Justice (NIJ) award (2015-MU-MU-K026) paved the way for significant progress towards this goal.

The goal of the previously funded project was to design an assay for mixture detection that could be multiplexed with the quantitation step of the forensic DNA workflow. Initial testing on a limited set of single source and 2-person 1:1 mixed samples using the Qiagen Rotor-Gene Q platform revealed that this quantitation-high resolution melt (HRM) integrated assay was able to accurately distinguish between single-source and mixture samples 94 percent or 100 percent of the time, depending on the analytical approach. Still, there remained several considerations that needed to be addressed prior to crime lab testing and implementation.

In order to more fully develop and assess the value of this emerging laboratory method, this study focused on the following goals:

  1. Test and evaluate the developed integrated mixture screening assay on the QuantStudio™ quantitative polymerase chain reaction (qPCR) platform, which is more consistent with instrumentation used in forensic practice.
  2. Complete select preliminary developmental validation studies to supplement the previously obtained proof-of-concept data.
  3. Development of an easy-to-use free, online tool for mixture prediction analysis.
  4. Testing of the developed integrated mixture screening assay with analysis tool in partner public forensic laboratory to assure direct applicability to lab practice.

Sample

Buccal swab samples for this work were part of the Virginia Commonwealth University forensic biological sample registry and were previously collected using sterile cotton swabs from donors.

Time Method

Cross-sectional

Universe

Previously collected DNA samples.

Data Type(s)

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Original Release Date

2024-08-28

Version History

2024-08-28 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.

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Notes

  • These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

  • The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.

  • ICPSR usually offers files in multiple formats for researchers to be able to access data and documentation in formats that work well within their needs. If you have questions about the accessibility of materials distributed by ICPSR or require further assistance, please visit ICPSR’s Accessibility Center.