How is PCR efficiency calculated and used for relative quantification?

The gold standard method for PCR efficiency estimation is a serial dilution of representative template (e.g. a mixture of RNA or cDNA from your samples).The PCR efficiency can be calculated from the slope of a serial dilution as follows: PCR efficiency= 10^(-1/slope) - 1.
The formula to go from Cq values to relative quantities is (E+1)^delta-Cq (hence 2^delta-Cq for an assay with 100% PCR efficiency).

In qbase+, users should provide the base of the exponential function as amplification efficiency value for relative quantification if they want to correct for target specific efficiency. The base number (E) is the efficiency value + 1, e.g. 1.95 for 95% efficiency (E value of 1.95).

Next to the gold standard method for PCR efficiency, there are a few algorithms (from the large number out there) that provide an estimate of the PCR efficiency based on a single amplification curve.
Importantly, the calculated results should be precise and accurate (and many algorithms fail in this respect). Hence, various papers (see references below) point at the danger of using sample specific PCR efficiencies based on a single amplification curve (or even replicate measurements).
The authors rather propose to average the sample specific efficiencies to obtain a target (gene) specific efficiency. This is also what we recommends to our users. LinRegPCR is a program that calculates Cq & efficiency values for fluorescent amplification curves & exports data in RDML file format that can be directly imported in qbase+.

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