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 tracki...
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MDPI AG
2025-01-01
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| author | Giulia Trastulli Giulia Calvino Bruno Papasergi Domenica Megalizzi Cristina Peconi Stefania Zampatti Claudia Strafella Carlo Caltagirone Emiliano Giardina Raffaella Cascella |
| author_facet | Giulia Trastulli Giulia Calvino Bruno Papasergi Domenica Megalizzi Cristina Peconi Stefania Zampatti Claudia Strafella Carlo Caltagirone Emiliano Giardina Raffaella Cascella |
| author_sort | Giulia Trastulli |
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| description | <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<sup>TM</sup> 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<sup>−15</sup>, 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<sup>TM</sup> 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. |
| format | Article |
| id | doaj-art-8766abd6777544bda543a46aff06e3ef |
| institution | Kabale University |
| issn | 2075-4418 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj-art-8766abd6777544bda543a46aff06e3ef2025-01-24T13:28:54ZengMDPI AGDiagnostics2075-44182025-01-0115214910.3390/diagnostics15020149Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample MonitoringGiulia Trastulli0Giulia Calvino1Bruno Papasergi2Domenica Megalizzi3Cristina Peconi4Stefania Zampatti5Claudia Strafella6Carlo Caltagirone7Emiliano Giardina8Raffaella Cascella9Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, ItalyGenomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, ItalyGenomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, ItalyGenomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, ItalyGenomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, ItalyGenomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, ItalyGenomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, ItalyDepartment of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, 00179 Rome, ItalyGenomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, ItalyGenomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy<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<sup>TM</sup> 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<sup>−15</sup>, 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<sup>TM</sup> 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.https://www.mdpi.com/2075-4418/15/2/149sample trackingOpenArray<sup>TM</sup> technologyRandom Match ProbabilityR for genetic dataR programming |
| spellingShingle | Giulia Trastulli Giulia Calvino Bruno Papasergi Domenica Megalizzi Cristina Peconi Stefania Zampatti Claudia Strafella Carlo Caltagirone Emiliano Giardina Raffaella Cascella Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring Diagnostics sample tracking OpenArray<sup>TM</sup> technology Random Match Probability R for genetic data R programming |
| title | Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring |
| title_full | Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring |
| title_fullStr | Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring |
| title_full_unstemmed | Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring |
| title_short | Sample Tracking Tool: A Comprehensive Approach Based on OpenArray Technology and R Scripting for Genomic Sample Monitoring |
| title_sort | sample tracking tool a comprehensive approach based on openarray technology and r scripting for genomic sample monitoring |
| topic | sample tracking OpenArray<sup>TM</sup> technology Random Match Probability R for genetic data R programming |
| url | https://www.mdpi.com/2075-4418/15/2/149 |
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