Fold change

[6] A disadvantage and serious risk of using fold change in this setting is that it is biased[7] and may misclassify differentially expressed genes with large differences (B − A) but small ratios (B/A), leading to poor identification of changes at high expression levels.

Furthermore, when the denominator is close to zero, the ratio is not stable, and the fold change value can be disproportionately affected by measurement noise.

In the field of genomics (and more generally in bioinformatics), the modern usage is to define fold change in terms of ratios, and not by the alternative definition.

This leads to more aesthetically pleasing plots, as exponential changes are displayed as linear and so the dynamic range is increased.

However, there is no mathematical reason to only use logarithm to base 2, and due to many discrepancies in describing the log2 fold changes in gene/protein expression, a new term "loget" has been proposed.

Volcano plot showing metabolomic data. The red arrows indicate points-of-interest that display both large magnitude fold-changes (x axis) and high statistical significance (-log10 of p value, y axis). The dashed red line shows where p = 0.05 with points above the line having p < 0.05 and points below the line having p > 0.05. This plot is colored such that those points having a fold-change less than 2 (log2 = 1) are shown in gray.