ArticlePloS one2019
A novel data processing method CyC* for quantitative real time polymerase chain reaction minimizes cumulative error.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 12 citations in OpenAlex.
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- MicroRNAs sequencing of plasma exosomes derived from patients with atrial fibrillation: miR-124-3p promotes cardiac fibroblast activation and proliferation by regulating AXIN1.Journal of physiology and biochemistry · 2022Article
- High resolution estimates of relative gene abundance with quantitative ratiometric regression PCR (qRR-PCR).The Analyst · 2021Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantitative real-time polymerase chain reaction (qPCR) is routinely conducted for DNA quantitative analysis using the cycle-threshold (Ct) method, which assumes uniform/optimum template amplification. In practice, amplification efficiencies vary from cycle to cycle in a PCR reaction, and often decline as the amplification proceeds, which results in substantial errors in measurement. This study reveals the cumulative error for quantification of initial template amounts, due to the difference between the assumed perfect amplification efficiency and actual one in each amplification cycle. The novel CyC* method involves determination of both the earliest amplification cycle detectable above background ("outlier" C*) and the amplification efficiency over the cycle range from C* to the next two amplification cycles; subsequent analysis allows the calculation of initial template amount with minimal cumulative error. Simulation tests indicated that the CyC* method resulted in significantly less variation in the predicted initial DNA level represented as fluorescence intensity F0 when the outlier cycle C* was advanced to an earlier cycle. Performance comparison revealed that CyC* was better than the majority of 13 established qPCR data analysis methods in terms of bias, linearity, reproducibility, and resolution. Actual PCR test also suggested that relative expression levels of nine genes in tea leaves obtained using CyC* were much closer to the real value than those obtained with the conventional 2-ΔΔCt method. Our data indicated that increasing the input of initial template was effective in advancing emergence of the earliest amplification cycle among the tested variants. A computer program (CyC* method) was compiled to perform the data processing. This novel method can minimize cumulative error over the amplification process, and thus, can improve qPCR analysis.
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