Abstract
The discrete Laplace method is recommended by multiple parties (including the International Society for Forensic Genetics, ISFG) to estimate the weight of evidence in criminal cases when a suspect's Y-STR profile matches the crime scene Y-STR profile. Unfortunately, modelling the distribution of Y-STR profiles in the population reference database is time-consuming and requires expert knowledge. When the suspect's Y-STR profile is added to the database, as would be the protocol in many cases, the parameters of the discrete Laplace model must be re-estimated. We found that the likelihood ratios with and without adding the suspect's Y-STR profile were almost identical with 1,000 or more Y-STR profiles in the database for Y-STR profiles with 8, 12, and 17 loci. Thus, likelihood ratio calculations can be performed in seconds if an established discrete Laplace model based on at least 1,000 Y-STR profiles is used. A match in a population reference database with 17 Y-STR loci from at least 1,000 male individuals results in a likelihood ratio above 10,000 in approximately 94% of the cases, and above 100,000 in approximately 82% of the cases. We offer free software accessible without restrictions to estimate a discrete Laplace model using a Y-STR reference database and subsequently to calculate likelihood ratios.
| Original language | English |
|---|---|
| Article number | 102839 |
| Journal | Forensic Science International: Genetics |
| Volume | 64 |
| ISSN | 1872-4973 |
| DOIs | |
| Publication status | Published - May 2023 |
Keywords
- Discrete Laplace
- Forensic genetics
- Weight of evidence
- Y-STR
- Y-chromosome
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Dive into the research topics of 'Weight of evidence of Y-STR matches computed with the discrete Laplace method: Impact of adding a suspect’s profile to a reference database'. Together they form a unique fingerprint.Research output
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Weight of evidence of Y-STR matches computed with the discrete Laplace method: Impact of adding a suspect’s profile to a reference database
Andersen, M. M., Eriksen, S. & Morling, N., 2022, bioRxiv, 24 p.Research output: Working paper/Preprint › Preprint
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