For GSEA analysis, we are familar with the above figure which shows the running enrichment score. But for most of the software, it lack of visualization method to summarize the whole enrichment result.
Leading edge analysis reports
Tags to indicate the percentage of genes contributing to the enrichment score,
List to indicate where in the list the enrichment score is attained and
Signal for enrichment signal strength.
It would also be very interesting to get the core enriched genes that contribute to the enrichment.
This is a feature request from clusterProfiler user. It’s similar to what I implemented in clusterProfiler for comparing biological themes. For comparing different enrichment results, the x-axis represent different gene clusters while for a single enrichment result, the x-axis can be gene count or gene ratio. This is actually similar to traditional barplot, with dot position as bar height and dot color as bar color. But dotplot can represent one more feature nicely by dot size and it can be a good alternative to barplot.
Disease Ontology (DO) provides an open source ontology for the integration of biomedical data that is associated with human disease. DO analysis can lead to interesting discoveries that deserve further clinical investigation.
DOSE was designed for semantic similarity measure and enrichment analysis.
Four information content (IC)-based methods, proposed by Resnik, Jiang, Lin and Schlicker, and one graph structure-based method, proposed by Wang, were implemented. The calculation details can be referred to the vignette of R package GOSemSim.