Our exploration of the co-occurrences of mutations in populations of viral genomes led us to propose several designs for the rapid identification of these co-occurrences. Identifying these co-occurrences is critical step to target potential therapies for fast-mutating viruses, especially those in the class of RNA viruses. Co-occurrences of mutations can indicate that the virus is successfully adapting to outside pressures, such as the host’s immune system.

We present a design study that looks at the problem of identifying potentially interesting co-occurrences of events (in this case, mutations), and show both a negative example (MatrixViewer) and a positive example (CooccurViewer) that helps analysts identify interesting co-occurrences.

This work was presented at EuroVis 2016 in Groningen, Netherlands.