Tool: pathfindR - Pathway Enrichment Analysis using Active Subnetworks
gravatar for egeulgen
11 months ago by
egeulgen660 wrote:

Hi all,

I would like to introduce our group's pathway enrichment package to you: pathfindR

  • This tool is designed to improve pathway enrichment analysis by firstly identifying active subnetworks in differential expression/methylation data using a protein-protein interaction network. It then performs pathway enrichment analysis (Over-Representation Analysis). By utilizing the interaction information, the tool identifies most of the involved pathways.
  • As of v1.1, pathfindR provides the gene sets KEGG, Reactome, BioCarta as well as GO-MF, GO-BP, GO-CC and GO-All (BP+MF+CC) for enrichment analysis
  • pathfindR also creates pathway diagrams for KEGG with the involved genes colored by change values. (this is achieved using the bioconductor package pathview)
  • The package allows for clustering of enriched pathways and establishment of representative pathways. This allows for further abstraction and reduces the complexity of analysis. The available clustering approaches are hierarchical and fuzzy.
  • As of v1.2, pathfindR provides functionality to score pathways for individual samples and plot a heatmap of the scores. This allows the user to gain insight into the activity of a pathway overall and per each sample.

You can download the package via CRAN.

You can read more about the package and a case study in our pre-print and read the pathfindR tutorial here.

ADD COMMENTlink modified 15 days ago • written 11 months ago by egeulgen660

It's useful.
1. Why not to bioconductor, containing lots of bioinformatics R packages instead of CRAN?
2. no examples of pathmap in the vignette.
3. An enhancement: Visualise the results of run_pathfindR, besides the table show.

Thank you.

ADD REPLYlink modified 9 months ago by zx87546.5k • written 9 months ago by Zhilong Jia1.4k

Thank you for the feedback! To answer them:

  1. We did not think it would make any difference
  2. We will try to include an example for pathmap in the next version
  3. The pathways are already visualized and can be viewed through the HTML reports. Would you expand on how we could provide more visualizations?

Thanks again,


ADD REPLYlink modified 9 months ago • written 9 months ago by egeulgen660
  1. Precision advertising. The targeting users of pathfindR are bioinformaticians, which are the users of Bioconductor, while the users of CRAN is R users. Getting more chance to encounter target audiences of pathfindR via Bioconductor. Anyway, not a problem.
  2. I did not check the HTML report as I cannot run the examples after installing pathfindR and filed an issue at Github. I mean the pathway enrichment itself, not visualization for each pathway based on pathview.
ADD REPLYlink written 9 months ago by Zhilong Jia1.4k

We’re looking into your issue on Github. We will try to include a visualization of the enrichment results in the next version (considering a bubble chart but feel free to share any ideas of what you had in mind).

ADD REPLYlink modified 8 months ago • written 9 months ago by egeulgen660

I will second the idea of a bubble chart. This is one of the easier/better GO packages to use that I've tried, but it lacks the visualization options of some others. Keep up the good work.

ADD REPLYlink written 6 months ago by jared.andrews071.8k

Can you please give a tutorial by taking some examples of a gene.

ADD REPLYlink modified 11 months ago • written 11 months ago by kalyanimeha30

You can see an example application in the vignette (browseVignettes("pathfindr_vignette")). We also have a wiki.

ADD REPLYlink modified 8 months ago • written 11 months ago by egeulgen660

HI This is a great package. I'm having a little trouble with the pathway scoring part of the tutorial. I'm not sure how to create the RA_exp_mat for my data?

thanks again

ADD REPLYlink written 6 months ago by amgodogma0

The expression matrix for the pathway scores is the same matrix as the one you use for differential expression analysis. Columns are samples, rows are genes and the values are expression values.

ADD REPLYlink written 6 months ago by egeulgen660
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