Why reporting Cq or delta-Cq is senseless

Jan M Ruijter
Academic Medical Center, Amsterdam, the Netherlands, The Netherlands

With the introduction of quantitative PCR (qPCR) it was assumed that the amplification efficiency, the fold-increase per cycle, was always close to 2. This simplification allowed the use of the so-called comparative Cq equation to calculate the fold-difference between target and reference genes in treated and control tissues. Over the years the original equation (2-ΔΔCq) seems to have lost its base and the minus sign. The remainder became so ingrained in qPCR-based papers that ‘ddCq’ currently seems to be the unit in which qPCR data are measured and have to be reported. However, the variations in annotation of the figure axes make that the presented data often cannot be interpreted.
The Cq value is defined by the general principle that the position of the amplification curve with respect to the cycle-axis, reflected in the Cq value, is a measure for the initial target quantity: the ‘later’ the curve, the higher the Cq value and the lower the starting quantity of the target-of-interest. However, this position is also dependent on the amplification efficiency. Therefore, reporting only ddCq implicitly accepts unvalidated assumptions about the amplification efficiencies involved. Reported Cq values can only be interpreted with the simplifying, and false, assumption that every PCR assay in the experiment is 100% efficient. Because of this assumption, the interpretation of Cq values always leads to an unknown bias.
The bias that is introduced by ignoring the actual PCR efficiency of target and reference genes can be prevented with the calculation of the so-called efficiency-corrected target quantities or fold-differences. This was already proposed in the early years of this millennium and is recommended in the MIQE guidelines. Indeed, such efficiency-corrected target quantities are reported by a number of qPCR data analysis methods published over a decennium ago. However, this need for efficiency-correction of qPCR results is still largely ignored by researchers, reviewers and publishers. This common shortcoming of the PCR research community may be the main reason for the limited reproducibility of reported qPCR results.

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