Development of a software for kinship analysis considering linkage and mutation based on a Bayesian network.

Area of Science:

• Forensic Genetics
• Computational Biology

Background:

• Forensic DNA testing increasingly uses more short tandem repeat (STR) loci for higher discrimination power.
• Kinship analysis must account for genetic linkage and mutation effects, which are not simultaneously addressed by existing software.

Purpose of the Study:

• To develop and validate KinBN, a novel freeware for kinship analysis in forensic DNA testing.
• To incorporate both linkage and mutation effects into a Bayesian network framework for likelihood ratio (LR) calculations.

Main Methods:

• Development of KinBN, a graphical-user-interface-based freeware utilizing Bayesian networks.
• Calculation of likelihood ratios (LRs) at multiple loci, considering linkage and mutation.
• Simulation of LR distributions for specified familial relationships.

Main Results:

• KinBN accurately calculates LRs, validated by comparison with existing software.
• The study evaluated the impact of linkage and mutation on LR values.
• Demonstrated the utility of KinBN in kinship analysis with expanded STR locus sets.

Conclusions:

• KinBN is a valuable tool for forensic kinship analysis, especially with large numbers of STR loci.
• The software effectively integrates linkage and mutation effects, improving analytical precision.
• KinBN provides a robust method for simulating LR distributions in complex forensic scenarios.