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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
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Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample

Giulia Trastulli1,2, Giulia Calvino1,3, Bruno Papasergi1

  • 1Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

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Summary

This study developed a cost-effective SNP genotyping protocol using OpenArray technology for reliable tracking of next-generation sequencing (NGS) samples. The method efficiently prevents errors and mix-ups in centralized genetic testing facilities.

Keywords:
OpenArrayTM technologyR for genetic dataR programmingRandom Match Probabilitysample tracking

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Area of Science:

  • Genomics
  • Molecular Biology
  • Laboratory Medicine

Background:

  • Centralizing genetic sequencing reduces diagnostic testing costs.
  • Specialized facilities require robust data quality verification and sample integrity.
  • Accurate sample tracking is crucial for reliable genetic testing.

Purpose of the Study:

  • Develop a protocol for tracking next-generation sequencing (NGS) analyzed samples.
  • Prevent errors and mix-ups in genetic testing procedures.
  • Ensure quality control, accuracy, and reliability in high-throughput genetic analysis.

Main Methods:

  • Utilized OpenArray technology for genotyping a panel of 60 single-nucleotide polymorphisms (SNPs).
  • Tested the protocol on 758 samples and validated on 100 samples.
  • Evaluated sample matching accuracy via simulation on 100 additional samples.

Main Results:

  • 55 probes achieved a call rate ≥90% for sample matching.
  • Developed an R tool for automated sample matching.
  • Achieved a random match probability of 3.29 × 10⁻¹⁵, demonstrating high discriminatory power.

Conclusions:

  • OpenArray technology offers cost-effectiveness, rapid analysis, and high discriminative power for sample tracking.
  • This SNP genotyping method is suitable for centralized genetic testing.
  • The protocol minimizes risks associated with laboratory centralization and high sample volumes.