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Published on: April 4, 2018
Comparison of Algorithms for Kinship Inference Using the Verogen ForenSeq® Kintelligence Kit
Ciara Di Scala1, Kelly Grisedale2, Jodie Ward1,3,4
1Centre for Forensic Science, School of Mathematical and Physical Sciences, Faculty of Science, University of Technology, Sydney, NSW 2007, Australia.
Background/Objectives:
Forensic kinship analysis is a rapidly developing practice that uses genetic data to identify unknown persons of interest through their genetic relatives. It can be used to generate new leads in forensic investigations, especially those involving long-term missing persons and unidentified human remains. More recently, the advent of SNP profiling panels designed specifically for forensic use has led to the exploration of kinship analysis using medium-density SNP data. This study aimed to evaluate the extent to which genetic relationships could be inferred using such data, and to assess the performance of different kinship inference methods.
Methods:
Kinship analysis was performed with both real and simulated profiles using the panel of SNPs contained within the Verogen ForenSeq® Kintelligence Kit, with a wide range of relationship types and seven types of kinship inference methods.
Results:
It was determined that kinship inferences were possible out to the fourth degree of kinship, and all inference methods analysed were equally effective when tested using simulated data. However, some variation between methods was observed when they were analysed using real sample data, suggesting that further study is needed using a larger sample size.
Conclusions:
The results of this study demonstrate that medium-density SNP data is sufficient for extended kinship inference out to the fourth degree, and that several kinship inference methods are suitable for use with the Verogen ForenSeq® Kintelligence Kit. These findings will support its application in forensic investigations involving the inference of distant genetic relationships.
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