On the use of dense sets of SNP markers and their potential in relationship inference
Abstract
With the advent of high density SNP arrays and the progress of next generation sequencing, demands for new methods to handle the subsequent data analysis have exploded. Forensic laboratories are generally hesitant to implement new methods in casework unless they are thoroughly tested and validated. This is particularly true when a third party contractor is involved in the analysis. In this paper we explore data from dense sets of SNP markers and study how different errors could potentially affect the results. Particularly, we study the effects of genotyping errors, linkage disequilibrium as well as the use of inappropriate population frequencies. We demonstrate that ignoring these concepts may lead to false conclusions for some different relationship cases and outline solutions to mitigate these problems.
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Results of the pairwise LR comparisons were largely inconclusive and provided limited support (LR << 10) for either hypothesis with all marker selections, which may indicate that even more markers would be necessary to resolve this case.
“Results were largely inconclusive and provided limited support (LR < < 10) [45] for either hypothesis with all marker selections, which may indicate that even more markers would be necessary to resolve this case [18].”
From Resolving a 150-year-old paternity case in Mormon history using DTC autosomal DNA testing of distant relatives. (2019) · cites this paper as [18]
Exceedance probability simulations have shown that high LR results are possible in very distant true relations of individuals.
“Exceedance probability simulations have shown that high LR results are possible in very distant true relations of individuals [18].”
From Resolving a 150-year-old paternity case in Mormon history using DTC autosomal DNA testing of distant relatives. (2019) · cites this paper as [18]
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Self-citation
- Authors
- Kling, D.
- Affiliations
- Oslo University Hospital (NO)
- Corresponding author
- Kling, Daniel
- ORCID
- Kling, Daniel
- Venue
- Forensic Science International: Genetics
- Publisher
- Elsevier BV
- Published
- 2019-03
- Volume
- 39
- Pages
- 19-31
- ISSN
- 1872-4973 (ISSN-L)
- OpenAlex
- W2902462595
- Cited by
- 41
- References
- 40
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 10 · 2023: 5 · 2022: 5 · 2021: 5 · 2020: 3 · 2019: 2
- FWCI
- 1.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Forensic Science International Genetics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- relationship inference, forensic genetics, genotyping errors, linkage disequilibrium, population allele frequencies, kinship analysis, error propagation
- MeSH terms
- False Positive Reactions, Genetic Markers, Genetics, Population, Humans, Pedigree, Linkage Disequilibrium, Likelihood Functions, Polymorphism, Single Nucleotide, Databases, Genetic, Forensic Genetics, Genotyping Techniques
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