How to visualize shared pathways between ORA (enrichment) results?

Question

[Picasa]

Hi,

I performed an over-representation analysis (ORA) separately for my differentially expressed genes, dividing them into upregulated and downregulated genes. Since I have two datasets, I generated 2 ORA results for upregulated genes and 2 ORA results for downregulated genes.

I noticed some common pathways between the two ORA results for the upregulated genes.

What are some good ways to summarize and visualize these results, especially to highlight the shared pathways but with keeping information about the 2 datasets (and in the future, more than 2 datasets) ?

Could you suggest example papers or R packages that might be helpful for creating these visualizations?

Thank you in advance!

[Dunois]

A Venn diagram or an Upset plot might work, I guess?

[Picasa]

I was thinking more about biological network :)

Answer 1

[Kevin Blighe]

Hi Picasa,

To summarise and visualize your ORA results while highlighting shared pathways across datasets, start with heatmaps that list pathways as rows and datasets as columns, colouring cells by metrics like -log10(p-value) or fold enrichment—this clusters similar pathways and reveals overlaps at a glance, while keeping dataset distinctions clear. For scalability to more datasets, supplement with UpSet plots to depict intersections of enriched pathways, then use faceted dotplots or bubble plots to drill down into per-dataset details like gene counts or adjusted p-values.

The clusterProfiler package in R shines here; its compareCluster function takes multiple gene lists as input and outputs ready-made comparative visuals like dotplots or heatmaps that emphasize consistencies and differences. For integrative analysis across datasets, try the ActivePathways package, which prioritizes shared pathways via data fusion and includes network-based plots.

Helpful papers include Paczkowska et al. (2020) in Nature Communications, which details ActivePathways for multi-omics pathway integration, and Reimand et al. (2019) in Nucleic Acids Research, showcasing enrichment maps in g:Profiler for visualizing overlaps in Cytoscape.

Best,
Kevin