Development of Publicly Available Forensic DNA Sequence Mixture Data

Published

March 12, 2025

Author(s)

Erica Romsos, Kevin Kiesler, Carolyn Steffen, Lisa Borsuk, Sarah Riman, Lauren Mullen, Jodi Irwin, Peter Vallone, Katherine Gettings

Abstract

Background: In 2018, the Next-Generation Sequencing Committee of SWGDAM queried bioinformatic and statistical interpretation method developers regarding data needs for the development of sequence-based probabilistic genotyping software. Methods: Based on this engagement, a set of 74 mixture samples was conceived and created using 11 single-source samples. The allelic overlap among these samples was evaluated and sample combinations of varying complexity were selected, aiming to represent the variability observed in forensic casework. Results: The samples were distributed into a 96-well plate design containing several features: (1) three-person mixtures of 1% to 5% minor components in triplicate with varying levels of input DNA to provide information on sensitivity and reproducibility, (2) three-person mixtures containing degraded DNA of either only the major contributor or all three contributors, (3) four- and five-person mixtures with varying ratios and donors, (4) a single-source dilution series. Conclusions: Mixture samples were prepared and have been sequenced thus far with three commercially available kits targeting forensic short tandem repeat (STR) and single nucleotide polymorphism (SNP) markers, with FASTQ data files and metadata publicly available at doi.org/10.18434/M32157.

Citation

Genes

Pub Type

Journals

Download Paper

https://doi.org/10.3390/genes16030333

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Keywords

forensic DNA, sequencing, training data, validation, bioinformatics, mixtures

Citation

Romsos, E. , Kiesler, K. , Steffen, C. , Borsuk, L. , Riman, S. , Mullen, L. , Irwin, J. , Vallone, P. and Gettings, K. (2025), Development of Publicly Available Forensic DNA Sequence Mixture Data, Genes, [online], https://doi.org/10.3390/genes16030333, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959432 (Accessed October 6, 2025)