One thing I didn’t do last year on this blog is reviewing papers. The reason is not just that I was lazy, but probably I put too much effort into one review post. That makes the post become a burden, and frequency of writing reviews reduced. So, keeping review articles simple enough looks important. The purpose of review posts on this blog is archiving what I think interesting and worth sharing with others. Over-emphasis of details is not necessary for this purpose.
I will re-start writing reviews of bioinformatic papers keeping this in mind.
Visualizing the information of multiple conflicting phylogenetic trees is a difficult task. The phylogenetic network is maybe the most frequently used, but its visual interpretation is not always straightforward. The Iwasaki&Takagi (2010) paper proposed an alternative method, called “centroid wheel tree”, to do this task.
The centroid wheel tree (CWT) is based on a consensus tree of multiple trees. Its difference from the ordinary consensus is orders of branches. Instead of placing them randomly, branches descending from an unresolved node are placed in a order where more often grouped branches are placed closer. This circular ordering on a node and numbers between branches present the information of frequency of occurrence of clades. Once you get used to how to read a CWT, you find it contains most information you need to interpret results of phylogenetic analyses.
I think CWT is one of the best phylogenetic methods I have seen. It visualizes complicated information in a simple, but informative way. However, it is not very widely used, unfortunately. (At least, I haven’t seen CWTs in any phylogenetic litereture.) A possible reason is that it is not implemented in major phylogenetic analysis packages or simply it is not known by biologist community.