Abstract
The weight of DNA evidence for forensic applications is typically assessed through the calculation of the likelihood ratio (LR). In the standard workflow, DNA is extracted from a collection of cells where the cells of an unknown number of donors are mixed. The DNA is then genotyped, and the LR is calculated through well-established methods. Recently, a method for calculating the LR from single-cell data has been presented. Rather than extracting the DNA while the cells are still mixed, single-cell data is procured by first isolating each cell. Extraction and fragment analysis of relevant forensic loci follows such that individual cells are genotyped. This workflow leads to significantly stronger weights of evidence, but it does not account for extracellular DNA that could also be present in the sample. In this paper, we present a method for calculation of an LR that combines single-cell and extracellular data. We demonstrate the calculation on example data and show that the combined LR can lead to stronger conclusions than would be obtained from calculating LRs on the single-cell and extracellular DNA separately.
Original language | English (US) |
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Pages (from-to) | 1-6 |
Number of pages | 6 |
Journal | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
DOIs | |
State | Accepted/In press - 2024 |
All Science Journal Classification (ASJC) codes
- Biotechnology
- Genetics
- Applied Mathematics
Keywords
- Biomedical signal processing
- Clustering algorithms
- DNA
- DNA
- Distributed databases
- Extracellular
- Forensics
- Sociology
- Statistics
- clustering algorithms
- maximum a posteriori estimation
- statistical analysis