Trastulli Giulia, Calvino Giulia, Papasergi Bruno, Megalizzi Domenica, Peconi Cristina, Zampatti Stefania, Strafella Claudia, Caltagirone Carlo, Giardina Emiliano, Cascella Raffaella
Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Department of Systems Medicine, Tor Vergata University, 00133 Rome, Italy.
Diagnostics (Basel). 2025 Jan 10;15(2):149. doi: 10.3390/diagnostics15020149.
: Centralizing genetic sequencing in specialized facilities is pivotal for reducing the costs associated with diagnostic testing. These centers must be able to verify data quality and ensure sample integrity. This study aims at developing a protocol for tracking NGS-analyzed samples to prevent errors and mix-ups, ensuring proper quality control, accuracy, and reliability in genetic testing procedures. To this purpose, a protocol based on the genotyping of a panel of 60 single-nucleotide polymorphisms (SNPs) by OpenArray technology was employed. : The protocol was initially tested on a cohort of 758 samples and subsequently validated on a cohort of 100 samples. Furthermore, its ability to accurately detect identical and different samples was evaluated through a simulation test conducted on an additional 100 samples. : In total, 55 probes achieved a call rate ≥90% and were subjected to the sample matching process performed by an R tool specifically developed. The SNP panel achieved a random match probability of 3.29 × 10, proving its suitability for efficiently tracking samples and rapidly identifying any errors or mix-up during the analytical processing. : The features of OpenArray technology, cost-effectiveness, rapid analysis, and high discriminative power make it a suitable tool for sample tracking. In conclusion, this method represents a valuable example for promoting laboratory centralization and minimizing the risks related to different laboratory procedures and the management of a high number of samples.
在专门设施中集中进行基因测序对于降低诊断测试相关成本至关重要。这些中心必须能够验证数据质量并确保样本完整性。本研究旨在制定一种用于追踪经二代测序(NGS)分析的样本的方案,以防止错误和混淆,确保基因检测程序中的适当质量控制、准确性和可靠性。为此,采用了一种基于通过OpenArray技术对一组60个单核苷酸多态性(SNP)进行基因分型的方案。该方案最初在758个样本的队列中进行测试,随后在100个样本的队列中进行验证。此外,通过对另外100个样本进行模拟测试,评估了其准确检测相同和不同样本的能力。总共55个探针的检出率≥90%,并由专门开发的R工具进行样本匹配过程。该SNP面板的随机匹配概率为3.29×10,证明其适用于有效追踪样本并在分析过程中快速识别任何错误或混淆。OpenArray技术的特点、成本效益、快速分析和高鉴别力使其成为样本追踪的合适工具。总之,该方法是促进实验室集中化并将与不同实验室程序和大量样本管理相关的风险降至最低的一个有价值的范例。