DNAc: A Clustering Method for Identifying Kinship Relations Between DNA Profiles Using a Novel Similarity Measure*

Abstract

After decades of refinement, DNA testing methods have become essential tools in forensic sciences. They are essentially based on likelihood ratio test principle, which is utilized specifically, by using as prior knowledge the allele frequencies in the population, to confirm or refute a given kinship hypothesis made on two genotypes. This makes these methods ill suited when allele frequencies or kinship hypotheses are unavailable. In this paper, we introduce DNAc, a new clustering methodology for DNA testing based on a new similarity measure that allows an accurate retrieval of the degree of relatedness among two or more genotypes, without relying on kinship hypotheses or allele frequencies in the population. We used DNAc in analyzing microsatellite DNA sequences distributed among 12 genotypes from normal individuals from two distinct families. The results show that DNAc accurately determines kinship among genotypes and further gathers them in the appropriate kinship groups.