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Semi-quantitative group testing for efficient and accurate qPCR screening of pathogens with a wide range of loads

2024-12Artigo científico Acesso aberto
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dc.contributor.authorNambiar, Ananthan
dc.contributor.authorPan, Chao
dc.contributor.authorRana, Vishal
dc.contributor.authorCheraghchi, Mahdi
dc.contributor.authorRibeiro, João
dc.contributor.authorMaslov, Sergei
dc.contributor.authorMilenkovic, Olgica
dc.contributor.institutionNOVALincs
dc.contributor.institutionFaculdade de Ciências e Tecnologia (FCT)
dc.contributor.pblBioMed Central (BMC)
dc.date.accessioned2025-02-14T21:19:36Z
dc.date.available2025-02-14T21:19:36Z
dc.date.issued2024-12
dc.descriptionFunding Information: The work was supported by NSF Grants 2107344 and 2107345. Publisher Copyright: © The Author(s) 2024.
dc.description.abstractBackground: Pathogenic infections pose a significant threat to global health, affecting millions of people every year and presenting substantial challenges to healthcare systems worldwide. Efficient and timely testing plays a critical role in disease control and transmission prevention. Group testing is a well-established method for reducing the number of tests needed to screen large populations when the disease prevalence is low. However, it does not fully utilize the quantitative information provided by qPCR methods, nor is it able to accommodate a wide range of pathogen loads. Results: To address these issues, we introduce a novel adaptive semi-quantitative group testing (SQGT) scheme to efficiently screen populations via two-stage qPCR testing. The SQGT method quantizes cycle threshold (Ct) values into multiple bins, leveraging the information from the first stage of screening to improve the detection sensitivity. Dynamic Ct threshold adjustments mitigate dilution effects and enhance test accuracy. Comparisons with traditional binary outcome GT methods show that SQGT reduces the number of tests by 24% on the only complete real-world qPCR group testing dataset from Israel, while maintaining a negligible false negative rate. Conclusion: In conclusion, our adaptive SQGT approach, utilizing qPCR data and dynamic threshold adjustments, offers a promising solution for efficient population screening. With a reduction in the number of tests and minimal false negatives, SQGT holds potential to enhance disease control and testing strategies on a global scale.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent2250589
dc.identifier.doi10.1186/s12859-024-05798-3
dc.identifier.issn1471-2105
dc.identifier.otherPURE: 106547443
dc.identifier.otherPURE UUID: 3bc0972c-317c-4c9c-a70a-03cc536f6e9f
dc.identifier.otherScopus: 85193514459
dc.identifier.otherPubMed: 38760692
dc.identifier.otherWOS: 001227047400001
dc.identifier.urihttp://hdl.handle.net/10362/179063
dc.identifier.urlhttps://www.scopus.com/pages/publications/85193514459
dc.language.isoeng
dc.peerreviewedyes
dc.subjectCOVID-19
dc.subjectCt values
dc.subjectGroup testing
dc.subjectPooled testing
dc.subjectqPCR
dc.subjectSemiquantitative group testing
dc.subjectViral load
dc.subjectStructural Biology
dc.subjectBiochemistry
dc.subjectMolecular Biology
dc.subjectComputer Science Applications
dc.subjectApplied Mathematics
dc.titleSemi-quantitative group testing for efficient and accurate qPCR screening of pathogens with a wide range of loadsen
dc.typejournal article
degois.publication.issue1
degois.publication.titleBMC Bioinformatics
degois.publication.volume25
dspace.entity.typePublication
rcaap.rightsopenAccess

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