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A likelihood ratio framework for inferring close kinship from dynamically selected SNPs.
Jianye Ge1, Bruce Budowle1,2,3, Michael Cariaso1
1Othram Inc., The Woodlands, TX, United States.
Frontiers in Genetics
|August 7, 2025
Summary
Forensic genetic genealogy (FGG) now integrates likelihood ratio (LR) calculations for robust human identification. This new method uses selected single nucleotide polymorphisms (SNPs) to accurately determine familial relationships in forensic investigations.
Area of Science:
- Forensic Science
- Genetics
- Human Identification
Background:
- Forensic genetic genealogy (FGG) uses single nucleotide polymorphism (SNP) data for human identification.
- Widespread adoption by forensic professionals requires likelihood ratio (LR)-based testing, aligning with kinship analysis standards.
Purpose of the Study:
- To develop and validate a novel method integrating LR calculations into FGG and SNP testing workflows.
- To enhance the reliability and statistical rigor of forensic human identification using genetic data.
Main Methods:
- Developed a dynamic SNP selection process based on minor allele frequency (MAF) and genetic distance.
- Utilized a curated panel of 222,366 SNPs from gnomAD v4 and the 1,000 genomes project.
- Implemented LR calculations for relationship testing in forensic genetic genealogy.
Main Results:
- Achieved high accuracy in resolving relationships up to second-degree relatives.
- A subset of 126 informative SNPs demonstrated 96.8% accuracy and a 0.975 F1 score across 2,244 pairs.
- The LR-based approach provides robust statistical support for close-relationship comparisons.
Conclusions:
- The novel LR-based methodology enables forensic laboratories to adopt modern genomic data within accredited frameworks.
- This enhances the rigor and statistical validity of FGG and SNP-based human identification.
- Facilitates broader adoption of advanced genetic techniques in forensic casework.
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