This post will show how to configure quickly the colors for the annotation of rows/columns that go on top or on the side of a heatmap.
That figure shows a difference of 4 between the two groups. Since 4 is twice than 2, we have a lying factor of 2.
Probably you think that this is not happening anywhere, it is ridiculous. It is, but probably you will find one of these cases in the news every day.
Moreover, this is happening in science as well. For instance a (Nature) paper which explains how authors are improving a method that analyzes NGS data.
They visualised a matrix correlation of the data using one method or another (b or c).
If you only read colours, you won’t see much difference, but there is. The problem was to use a different colour scale to show the same type of data. Probably they were produced separately, so the command to produce those figures (probably an R function) had to guess the scale by its own, resulting that 0.89 is equal to 0.75 .
I leave my post here, and may say: take some time to think about it.