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About qPCR Data Analysis: From Amplification Curve to Defensible Fold Change

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Learn to turn raw real-time PCR fluorescence traces into quantitative results you can defend. You will set baselines and thresholds correctly, read Cq values, build standard curves and derive amplification efficiency from the slope, choose between absolute and relative quantification, and apply the 2^-ddCt and Pfaffl models knowing exactly which efficiency assumption each one makes. You will also validate reference genes, use melt curves and control reactions to prove specificity and rule out genomic DNA, place variance in the right replicate layer, and report the whole experiment to MIQE standards.

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What You'll Learn

Concepts:
Amplification Efficiency from Standard Curve Slope No-Reverse-Transcriptase Control Technical Versus Biological Replicates Reference Gene Selection and Validation Dynamic Range and Limit of Detection in qPCR Quantification Cycle qPCR Amplification Curve Phases Absolute Versus Relative Quantification Baseline and Threshold Setting in qPCR 2^-ddCt Method Pfaffl Method Exponential Amplification Assumption in qPCR Melt Curve Analysis qPCR Standard Curve No-Template Control and Primer-Dimer Detection MIQE Guidelines

What you will learn

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