Statistical analysis of real-time PCR data |
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| Authors: | Joshua S Yuan Ann Reed Feng Chen and C Neal Stewart |
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| Institution: | (1) Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA;(2) University of Tennessee Institute of Agriculture Genomics Hub, University of Tennessee, Knoxville, TN 37996, USA;(3) Statistical Consulting Center, University of Tennessee, Knoxville, TN 37996, USA |
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| Abstract: | Background Even though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of
quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval
and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the
standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models
for the analysis of real-time PCR data. |
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