  Contemporary techniques in biology produce readouts for large numbers of
genes simultaneously, the typical example being differential gene expression
measurements. Moreover, those genes are often richly annotated using GO terms
that describe gene function and that can be used to summarize the results of
the genome-scale experiments. However, making sense of such GO enrichment
analyses may be challenging. For instance, overrepresented GO functions in a
set of differentially expressed genes are typically output as a flat list, a
format not adequate to capture the complexities of the hierarchical structure
of the GO annotation labels.
  In this chapter, we survey the various methods to visualize large,
difficult-to-interpret lists of GO terms. We catalogue their availability
(web-based or standalone), the main principles they employ in summarizing large
lists of GO terms, and the visualization styles they support. These brief
commentaries on each software are intended as a helpful inventory, rather than
comprehensive descriptions of the underlying algorithms. Instead, we show
examples of their use and suggest that the choice of an appropriate
visualization tool may be crucial to the utility of GO in biological discovery.
