Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring

<b>Background/Objectives</b>: 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^TM technology was employed. <b>Methods</b>: 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. <b>Results</b>: 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^-15, proving its suitability for efficiently tracking samples and rapidly identifying any errors or mix-up during the analytical processing. <b>Conclusions</b>: The features of OpenArray^TM 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.