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Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays
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We use high-density single nucleotide polymorphism (SNP) genotyping microarrays to demonstrate the ability to accurately and robustly determine whether individuals are in a complex genomic DNA mixture. We first develop a theoretical framework for detecting an individual's presence within a mixture, then show, through simulations, the limits associated with our method, and finally demonstrate experimentally the identification of the presence of genomic DNA of specific individuals within a series of highly complex genomic mixtures, including mixtures where an individual contributes less than 0.1% of the total genomic DNA. These findings shift the perceived utility of SNPs for identifying individual trace contributors within a forensics mixture, and suggest future research efforts into assessing the viability of previously sub-optimal DNA sources due to sample contamination. These findings also suggest that composite statistics across cohorts, such as allele frequency or genotype counts, do not mask identity within genome-wide association studies. The implications of these findings are discussed.
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“However, this rapidly evolving research arena has been accompanied by equally rapid confirmation that genomic data can never be truly anonymized. A steady stream of provocative studies (51, 62, 68, 122) has demonstrated that it is possible to discover the identities of individuals whose genomic data had otherwise been considered deidentified.”
From Lessons from HeLa Cells: The Ethics and Policy of Biospecimens (2016) · cites this paper as [62]
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Metadata
- Authors
- Homer, N., Szelinger, S., Redman, M., Duggan, D., Tembe, W., Muehling, J., Pearson, J. V., Stephan, D. A., Nelson, S. F., & Craig, D. W.
- Affiliations
- Translational Genomics Research Institute (US)
- University of California, Los Angeles (US)
- Corresponding author
- Craig, David W.
- ORCID
- Venue
- PLoS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2008-08-29
- Volume
- 4
- Issue
- 8
- Pages
- e1000167
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- PMC
- PMC2516199
- OpenAlex
- W2040228409
- Cited by
- 1,221
- References
- 21
- Citations by year
- 2026: 24 · 2025: 42 · 2024: 54 · 2023: 71 · 2022: 81 · 2021: 76 · 2020: 89 · 2019: 103 · 2018: 87 · 2017: 81 · 2016: 65 · 2015: 59 · 2014: 79 · 2013: 62 · 2012: 63
- FWCI
- 34.85
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Genetics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Wellcome Trust (076113)
- Translational Genomics Research Institute
- National Institutes of Health
- National Heart, Lung, and Blood Institute (U01HL086528)
- 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
- DNA mixture analysis, single nucleotide polymorphisms, forensic DNA identification, sample contamination, genome-wide association study
- MeSH terms
- Computer Simulation, Genetics, Medical, Genotype, Humans, Genome, Human, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide
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