Semi-Quantitative Group Testing for Efficient and Accurate qPCR Screening of Pathogens with a Wide Range of Loads
July 31, 2023 Β· Declared Dead Β· π BMC Bioinformatics
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Authors
Ananthan Nambiar, Chao Pan, Vishal Rana, Mahdi Cheraghchi, JoΓ£o Ribeiro, Sergei Maslov, Olgica Milenkovic
arXiv ID
2307.16352
Category
q-bio.QM
Cross-listed
cs.IT,
stat.ME
Citations
0
Venue
BMC Bioinformatics
Last Checked
3 months ago
Abstract
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. 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 $24$% while maintaining a negligible false negative rate.
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