In relative quantification with Real Time PCR (qRT-PCR,), accurate analysis requires equal amplification efficiency for both genes (Gene of interest and reference gene) and equal threshold values for all the samples. In this quantification method the expression level in treated samples will be calculated in comparison to the control group. We conducted the present study to design an algorithm for converting the data obtained from different runs containing identical standard samples into one run with the same amplification efficiency and threshold value. For this purpose, two formulas were designed; one to convert the amplification efficiency of the each run to 100%, and the other one for converting data from different runs into one run. Utilizing these two formulas, an algorithm was developed and named CtNorm. The online version of CtNorm algorithm is available at http://ctnorm.sums.ac.ir/. We used qRT-PCR technique to validate the accuracy of the designed algorithm for the normalization of four different human internal control genes. Normalizing the Ct values obtained from separate runs with the CtNorm algorithm has eliminated the differences and the average of the Ct values has become similar to the condition in which all the samples were amplified in a single run. The CtNorm algorithm could be utilized for equalizing the Ct values of several qRT-PCR runs with the same standard samples. The algorithm has also the ability to convert the amplification efficiency to 100% which is useful in absolute and relative quantification.

在使用实时 PCR (qRT-PCR) 进行相对定量时，准确分析需要两个基因（目标基因和参考基因）的扩增效率相同，并且所有样本的阈值相同。在该定量方法中，将计算处理样品中的表达水平与对照组相比。我们进行了本研究以设计一种算法，用于将从包含相同标准样品的不同运行中获得的数据转换为具有相同扩增效率和阈值的一次运行。为此，设计了两个公式；一个将每次运行的扩增效率转换为 100%，另一个将来自不同运行的数据转换为一次运行。利用这两个公式，开发了一种算法并命名为 CtNorm。http://ctnorm.sums.ac.ir/。我们使用 qRT-PCR 技术来验证设计算法的准确性，用于四种不同的人类内部控制基因的归一化。使用 CtNorm 算法对从单独运行中获得的 Ct 值进行归一化消除了差异，并且 Ct 值的平均值变得类似于在单次运行中扩增所有样品的条件。CtNorm 算法可用于均衡多个 qRT-PCR 运行与相同标准样品的 Ct 值。该算法还具有将扩增效率转换为 100% 的能力，这在绝对和相对定量中非常有用。