The determination of how much a quantity changes relative to its initial value, expressed on a logarithmic scale with a base of 2, allows for a standardized comparison of differential expression. For instance, if a gene’s expression level doubles from a control condition to an experimental condition, the resulting value is 1. Conversely, a halving of expression yields a value of -1. This transformation centers the data around zero, simplifying the identification of both up-regulated and down-regulated entities.
This method provides several advantages. It normalizes data, making it easier to visualize and interpret, especially when dealing with large variations in magnitude. It is widely used in genomics, transcriptomics, and proteomics to identify significant differences in gene or protein expression across different experimental conditions. Its utility stems from its ability to represent data symmetrically around zero, facilitating straightforward comparison and downstream analysis, while mitigating the impact of outliers.
