What is the linear derivative baseline correction and how is it calculated?
The linear derivative baseline correction was developed by Fluidigm to deal more effectively with correction for baseline drift in real-time PCR data. Typically, the baseline is modeled as a line as follows, where x is the PCR cycle, b is the slope and a is the y-intercept:
Baseline = a + b * x
In practice, it is difficult to accurately estimate the value of b. The error in estimating b introduces error in the determination of Ct values, especially at later cycles. The derivative correction takes advantage of the fact that the derivative of an exponential is an exponential, while the derivative of a line is a constant.
Using the linear derivative method, b can be easily estimated by the average value of the first few cycles. Furthermore, any error in estimating b does not have a progressively worse effect on determining Ct with increasing cycle number.
In the linear regression analysis method, calculation of the relative concentrations of unknown samples accounts for unequal efficiencies of target and control genes. Fluidigm provides user-friendly software for the automated analysis of high-throughput gene expression data by drawing relative standard curves for relative quantification, allowing the use of one or more reference genes for sample normalization.