Relative quantification of gene expression is dependent upon accurate normalization of data to one or more internal controls (ICs), which are typically housekeeping genes present and unchanged in all samples (Sturzenbaum and Kille, 2001). Issues related to normalization are discussed in greater detail in Chapter 4.
What is the most suitable internal control for qPCR? Unfortunately, no simple answer exists, as every IC has its own benefits and limitations, and what may be ideal in one experimental scenario may be unsuitable in others. Arguably, the most sensible approach to qPCR data normalization was provided by Vandesompele et al. (2002), who recommended using multiple ICs, enabling the reliability of these control genes to be assessed against each other. The geometric mean of the most reliable genes is then used in the form of a normalization factor (NFx, where x is the number of ICs used), which is less susceptible to distortion by outliers than the arithmetic mean.
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