Inferring the Degree of Relatedness and Kinship Types Using an All-in-One Marker Set.

ABSTRACT:

Background/objectives

Kinship inference is commonly adopted in various forensic applications, but previous studies have often lacked precision.

Methods

In this study, a new method for the nomenclature of kinship types, i.e., kinship chain (KC), was proposed, and then, six types of identity by state (IBS) scores were calculated for simulated and real families using four types of markers. Finally, several Bayesian network (BN)-based classifiers were constructed to investigate the efficiency of the kinship inference.

Results

A total of 7, 22, 58, and 3 KCs were obtained for common first-, second-, and third-degree relatives and unrelated pairs, respectively. High accuracies could be achieved in distinguishing between related and unrelated pairs after combining the four t

SUBMITTER: Li R 

PROVIDER: S-EPMC12026669 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature