R

Foreword We recently developed an R package, named {epistack}, to visualise epigenomic data. Epistack is available on github and Bioconductor. The best place to learn more about it is probably the package’s vignette.

In genomics, and in many other -omics or big data fields, we often try to plot big matrices. By big matrices, I mean matrices that have more columns and/or rows than pixels in your device.

Graphical abstract: Molecular biologists and biochemists are quite sensitive on the topic of DNA representation. Many of them will be triggered when the looping of the DNA is misrepresented as a left-handed helix instead of a right-handed one (what we mean by that is that when one looks at DNA from ‘within’ the helix, they turn clock-wise as they get more distant).

When sorting a large table according to a specific metric (let’s say gene expression value), it is frequent to have ties for certain values (for example, 0 expression values). In most version of sorting, the order of the ties is preserved by the sorting.