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Cited by 6Forensic and Genetic ResearchIdentification and Quantification in FoodClinical Laboratory Practices and Quality Control

Human sample authentication in biomedical research: comparison of two platforms

Open access
Manjunath, Harshitha Shobha, James, Nicola, Mathew, Rebecca, Al Hashmi, Muna, Silcock, Lee, Biunno, Ida, De Blasio, Pasquale, Manickam, Chidambaram +1 more·2021·Scientific Reports
DOI 10.1038/s41598-021-92978-3PMC PMC8263568
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Abstract

Samples used in biomedical research are often collected over years, in some cases from subjects that may have died and thus cannot be retrieved in any way. The value of these samples is priceless. Sample misidentification or mix-up are unfortunately common problems in biomedical research and can eventually result in the publication of incorrect data. Here we have compared the Fluidigm SNPtrace and the Agena iPLEX Sample ID panels for the authentication of human genomic DNA samples. We have tested 14 pure samples and simulated their cross-contamination at different percentages (2%, 5%, 10%, 25% and 50%). For both panels, we report call rate, allele intensity/probability score, performance in distinguishing pure samples and contaminated samples at different percentages, and sex typing. We show that both panels are reliable and efficient methods for sample authentication and we highlight their advantages and disadvantages. We believe that the data provided here is useful for sample authentication especially in biorepositories and core facility settings.

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  • SNP surveys detect contamination at or above 3%, and the cytochrome c oxidase I gene reveals contamination at or above 1%.

    “Alternatives surveying single nucleotide polymorphisms (”

    From The history, landscape, and outlook of human cell line authentication and security (2024) · cites this paper as [102]

    The Discussion reports that SNP-based profiling can detect intra-human cross-contamination as low as 2%, supporting the general point about SNP surveys. It does not establish a 3% threshold, and neither the Discussion nor the Results passages address detection using the cytochrome c oxidase I gene or a 1% threshold. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • The annual financial effect of CCCM is more than 15 times the overall funding of research by the American Cancer Society.

    “The annual financial effect of CCCM is more than 15 times the overall funding of research by the American Cancer Society[87,102].”

    From The history, landscape, and outlook of human cell line authentication and security (2024) · cites this paper as [102]

    The Introduction discusses sample misidentification and estimates the prevalence of cell-line contamination, but gives no annual financial impact. Searches for the American Cancer Society and a funding comparison found no passage supporting the claimed more-than-15-fold figure. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

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Cites

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Research works printed but not linked: 26

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Cited by

Sorted by citations

Authors
Manjunath, H. S., James, N., Mathew, R., Al Hashmi, M., Silcock, L., Biunno, I., De Blasio, P., Manickam, C., & Tomei, S.
Affiliations
Sidra Medical and Research Center (QA)
Corresponding author
Tomei, Sara
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2021-07-07
Volume
11
Issue
1
Pages
13982-13982
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-021-92978-3
PMC
PMC8263568
OpenAlex
W3180262757
Cited by
6
References
9
Citations by year
2026: 1 · 2025: 1 · 2024: 2 · 2023: 2
FWCI
0.56
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Identification and Quantification in Food
  • Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
Keywords
sample authentication, sample mix-up, sample cross-contamination, sex typing, sample misidentification
MeSH terms
Female, Humans, Male, Biological Specimen Banks, Microsatellite Repeats, Polymorphism, Single Nucleotide, Biomedical Research, Biometric Identification, DNA Contamination

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