qpcr calculation template is a qpcr calculation sample that gives infomration on qpcr calculation design and format. when designing qpcr calculation example, it is important to consider qpcr calculation template style, design, color and theme. because cq is directly related to the starting concentration of the target, and the difference in cq values is related to the starting concentration ratio, the only results of qpcr analysis reported are often cq, δcq or δδcq values. the uniform blue and orange triangles, from n0 to nq to cq, illustrate that for two sets of reactions with about 10-fold different starting concentrations and the same pcr efficiency; the difference in cq values is proportional to the difference in log(n0). the latter equation shows that the cq value of a reaction is not only determined by the target concentration (n0), but also by the pcr efficiency (e) [14] as well as the level of the quantification threshold (nq). this method is based on the commonly accepted rule of thumb that, with an input of 10 template copies in the reaction and a pcr efficiency between 1.8 and 2, a cq value of approximately 35 will be observed [16]. dividing the cq value of target a by the cq of target b is equivalent to dividing the logarithms of the starting concentrations of these two targets. rearrangement of equation (3) shows that the efficiency-corrected target quantity (n0) for each reaction can be calculated with the quantification threshold, the actual pcr efficiency and the cq value observed in the reaction [22,23]: when only cq values are reported in a paper, the reader has to interpret these values by assuming that the pcr was 100% efficient. the graph shows that at a cq of 28 and an actual efficiency of 1.7, the target quantity calculated with an efficiency of 2 is 100 times lower than it actually is (figure 3a, asterisk). the graph of this bias for different pcr efficiency values of the target and different cq values of the target was plotted for references with efficiency values of 1.7 and 1.9 and a cq value of 28 (figure 3b). this biased interpretation of cq values depends on the pcr efficiency values and the pcr efficiency difference between targets and references, which vary between assays and protocols.

## qpcr calculation format

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it is of importance to note that in clinical applications, a sample is often considered positive when the amplification curve reaches the quantification threshold (nq) and a cq value is called. this sdm value is derived from the fit of a sigmoidal function to the amplification data and reported as cq. as can be seen in equation (8), this calculation of the target quantity accounts for the actual threshold setting and pcr efficiency. because the number of copies in the wells is discrete, independent and random, this number will follow a poisson distribution. as shown in figure 6b, the pipetting error will lead to a cq range that is the same for every input; e.g., 15% pipetting error and pcr efficiency of 1.9 gives a cq range of 0.5 cycles for all inputs [15] (figure 6c). when a saturating dye is used, the contribution of the artefact to the observed fluorescence can be determined from the melting curves and used for correction of the observed cq and n0 values [11]. illustration of the cq values observed for different inputs and efficiency values. due to the inherent specifications of a qpcr machine, the volume of the assayed sample in the reaction is limited and ranges between 5 and 20 ml in size. the reporting of cq values must be discouraged—a cq value by itself is meaningless; δcq and δδcq are confusing and their interpretation leads to biased notions about the gene expression ratios and between-group effects found in the published experiment. all authors have read and agreed to the published version of the manuscript.