Two algorithms for biospecimen comparison and differentiation using SNP genotypes

Scott Morris, Esma Gel, Jordan V. Smith, Joseph D. Paulauskis, Dirk Van Den Boom, Paul Oeth, Robert Penny

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Aims: Biobanks are frequently required to verify specimen relationships. We present two algorithms to compare SNP genotype patterns that provide an objective, high-throughput tool for verification. Methods: The first algorithm allows for comparison of all holdings within a biobank, and is well suited to construct sample relationships de novo for comparison with assumed relationships. The second algorithm is tailored to oncology, and allows one to confirm that paired DNAs from malignant and normal tissues are from the same individual in the presence of copy number variations. To evaluate both algorithms, we used an internal training data set (n = 1504) and an external validation data set (n = 1457). Results: In comparison with the results from manual review and a priori knowledge of patient relationships, we identified no errors in interpreting sample relationships within our validation data set. Conclusion: We provide an efficient and objective method of automated data analysis that is currently lacking for establishing and verifying specimen relationships in biobanks. Original submitted 11 October 2012; Revision submitted 25 January 201.

Original languageEnglish (US)
Pages (from-to)379-390
Number of pages12
JournalPharmacogenomics
Volume14
Issue number4
DOIs
StatePublished - 2013

Keywords

  • SNP
  • biobanking
  • distance algorithm
  • human identification
  • loss of heterozygosity

ASJC Scopus subject areas

  • Molecular Medicine
  • Genetics
  • Pharmacology

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