Por favor, use este identificador para citar o enlazar este ítem: http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/2103
Improving Baseline Subtraction for Increased Sensitivity of Quantitative PCR Measurements
Paul N. Patrone.
Anthony J. Kearsley.
Erica L. Romsos.
Peter M. Vallone.
Acceso Abierto
Atribución-NoComercial-SinDerivadas
https://arxiv.org/pdf/2004.05466v1.pdf
Motivated by the current COVID-19 health-crisis, we examine the task of baseline subtraction for quantitative polymerase chain-reaction (qPCR) measurements. In particular, we present an algorithm that leverages information obtained from non-template and/or DNA extraction-control experiments to remove systematic bias from amplification curves. We recast this problem in terms of mathematical optimization, i.e. by finding the amount of control signal that, when subtracted from an amplification curve, minimizes background noise. We demonstrate that this approach can yield a decade improvement in sensitivity relative to standard approaches, especially for data exhibiting late-cycle amplification. Critically, this increased sensitivity and accuracy promises more effective screening of viral DNA and a reduction in the rate of false-negatives in diagnostic settings.
arxiv.org
2020
Artículo
https://arxiv.org/pdf/2004.05466v1.pdf
Inglés
VIRUS RESPIRATORIOS
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