Development of a software for kinship analysis considering linkage and mutation based on a Bayesian network
•We developed a new software program for kinship analysis called KinBN.•KinBN calculates likelihood ratios based on a Bayesian network.•KinBN simulates likelihood ratio distributions under the hypothesized relationship.•The program considers the effects of linkage and mutation. In forensic DNA testi...
Gespeichert in:
Veröffentlicht in: | Forensic science international : genetics 2020-07, Vol.47, p.102279-102279, Article 102279 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | •We developed a new software program for kinship analysis called KinBN.•KinBN calculates likelihood ratios based on a Bayesian network.•KinBN simulates likelihood ratio distributions under the hypothesized relationship.•The program considers the effects of linkage and mutation.
In forensic DNA testing, the number of tested short tandem repeat loci has increased owing to new multiplex kits with additional loci. Although this advancement provides improved discrimination power, the effects of linkage and mutation must be considered during kinship analysis. However, no software currently includes both of these effects. In this study, we developed new freeware called KinBN for kinship analysis based on a Bayesian network. The software is graphical-user-interface-based and calculates the likelihood ratios (LRs) at multiple loci considering the effects of linkage and mutation. In addition, the software can simulate the LR distribution according to the specified relationship. We confirmed the accuracy of KinBN by comparing its LRs with those of other software and evaluated the effects of linkage and mutation on the LRs. Our results indicate that KinBN is a useful tool for kinship analysis, particularly if expanded locus sets are used for DNA testing. |
---|---|
ISSN: | 1872-4973 1878-0326 |
DOI: | 10.1016/j.fsigen.2020.102279 |