Content area

Abstract

The calculation of the paternity index (PI) value of common bi-allelic genotypes at STR loci has been standardized in paternity cases. However, for tri-allelic patterns, a rare category of genotyping aberration in forensic practice, the statistical analysis in paternity testing remains disputed. The Type 1 tri-allelic pattern generally results from somatic mutation in the early stage of individual development. The Type 2 tri-allelic pattern is commonly generated by segmental duplication in the genome. In this study, practical and theoretical aspects of the evaluation of evidence concerning the Type 1 and Type 2 tri-allelic patterns in healthy individuals are discussed based on the likelihood ratio (LR) in different categories of kinship cases. The calculation of the PI value concerning tri-allelic genotypes is formulated according to the generation and genetic transmission of tri-allelic patterns. Meanwhile, a package tool named TriPI is developed to assist the calculation of the PI value in paternity testing concerning tri-allelic subjects, which could benefit the evaluation of the weight of evidence in the interpretation of tri-allelic pattern in forensic practice.

Details

Title
Calculation of the Paternity Index for STR with tri-allelic patterns in paternity testing
Author
Yang, Qinrui 1 ; Yao, Yining 1 ; Shao, Chengchen 1 ; Zhou, Yuxiang 1 ; Li, Hui 2 ; Li, Chengtao 3 ; Tang, Qiqun 4 ; Xie, Jianhui 1 

 Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China 
 Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China; Shanghai Key Laboratory of Crime Scene Evidence, Institute of Criminal Science and Technology, Shanghai Municipal Public Security Bureau, Shanghai 200083, China 
 Shanghai Key Laboratory of Forensic Medicine, Academy of Forensic Science, Ministry of Justice, Shanghai 200063, China 
 Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China 
Publication year
2021
Publication date
Jul 2021
Publisher
Elsevier Limited
e-ISSN
18726283
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2539509495
Copyright
©2021. Elsevier B.V.