Luna^® Universal qPCR & RT-qPCR – Experience best-in-class performance

Evaluating qPCR results: capturing performance as “dots in boxes”

NEB has developed a method to better evaluate the large amount of qPCR data generated in an experiment. The output of this analysis is known as a dot plot, and captures the key features of a successful, high-quality qPCR experiment as a single point. This method of analysis allows many targets and conditions to be compared in a single graph.

For each experiment, triplicate reactions are set up across a five-log range of input template concentrations (Amplification plot, bottom-left). Three non-template control (NTC) reactions are also included, for a total of 18 reactions per condition/target. Efficiency (%) is calculated (Standard curve, top-left) and is plotted against ΔC_q (dot plot, center), which is the difference between the average C_q of the NTC and the lowest input. This parameter captures both detection of the lowest input and non-template amplification. Acceptable performance criteria are defined as an Efficiency of 90-110% and a ΔC_q of ≥ 3 (green box).

Other performance criteria are captured using a 5-point Quality Score (top-right). Included are:

1. 1. Linearity of amplification, as indicated by the R² standard curve
2. 2. Reproducibility, as indicated by the consistency of triplicate C_q values for each input concentration
3. 3. Fluorescence consistency, as indicated by similar endpoint fluorescence (RFU_max)
4. 4. Curve steepness
5. 5. Sigmoid curve shape

Quality Score is represented by the size and fill of the plotted dot, with experiments that pass all performance criteria represented by a solid dot within the box. These scoring methods were built upon the MIQE qPCR/RT-qPCR guidelines (Bustin, S.A. et al. (2009) Clin Chem. 55, 611-22 and Trombley Hall, A. et al. (2013) PLoS One 8(9):e73845). An example of this analysis is shown below.