ArticlePloS one2016
Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Integrative linkage and recombination analysis of 25 X-STRs across 7 linkage groups using pedigree-based and SNP-based strategies.Frontiers in genetics · 2025Article
- Private detection of relatives in forensic genomics using homomorphic encryption.BMC medical genomics · 2024Article
- Article
- Validation of the Utility of the Genetically Shared Regions of Chromosomes (GD-ICS) Measuring Method in Identifying Complicated Genetic Relatedness.Journal of Korean medical science · 2024Article
- A novel approach of kinship determination based on the physical length of genetically shared regions of chromosomes.Genes & genomics · 2024Article
- Utility of ForenSeq™ DNA Signature Prep Kit in the research of pairwise 2nd-degree kinship identification.International journal of legal medicine · 2019Article
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Authors and funding
9 authors.
Funding
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Abstract
We developed a new approach for pairwise kinship analysis in forensic genetics based on chromosomal sharing between two individuals. Here, we defined "index of chromosome sharing" (ICS) calculated using 174,254 single nucleotide polymorphism (SNP) loci typed by SNP microarray and genetic length of the shared segments from the genotypes of two individuals. To investigate the expected ICS distributions from first- to fifth-degree relatives and unrelated pairs, we used computationally generated genotypes to consider the effect of linkage disequilibrium and recombination. The distributions were used for probabilistic evaluation of the pairwise kinship analysis, such as likelihood ratio (LR) or posterior probability, without allele frequencies and haplotype frequencies. Using our method, all actual sample pairs from volunteers showed significantly high LR values (i.e., ≥ 108); therefore, we can distinguish distant relationships (up to the fifth-degree) from unrelated pairs based on LR. Moreover, we can determine accurate degrees of kinship in up to third-degree relationships with a probability of > 80% using the criterion of posterior probability ≥ 0.90, even if the kinship of the pair is totally unpredictable. This approach greatly improves pairwise kinship analysis of distant relationships, specifically in cases involving identification of disaster victims or missing persons.
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