This rescaling and rotation allows for better visibility and emphasis of important outliers points that vary between the two measurement conditions.
If we modify our original a (or b) vector via: where then R and A can be defined as: R, like M, is plotted on the y-axis and represents a log (fold change) ratio between a and b.
The RA plot provides a quick overview of the distribution and size of a dataset consisting of non-zero counts.
This characteristic arrow-like shape derives from two key features: on the right at the vector origin, a long asymptotic tail, and on the left (forming the arrow head) two (often dense) patches of condition-unique points.
Because a large portion of the pairs of a and b contain zeros in one or both conditions, they are impossible to plot as-is on a log scale.