ClusterProfiler-cnetplot output to Cytoscape?

Question

[EdS]

I have just started using the clusterProfiler (R) package for graphical display of pathway analysis. The "cnetplot" function provides a very good display of GO-terms and associated genes, however for larger pathways/larger # of genes - the graphical output often is too dense, and names/links are obscured. Is there any way to send output of cnetplot to Cytoscape (or some equivalent method) so that graphical output can be manipulated and rearranged?

Thanks for any ideas,

Answer 1

[Guangchuang Yu]

1. you can use cnetplot(fixed=FALSE) then you can drag nodes and rearrange them.

2. you can save the object by x <- cnetplot(), then the underlaying igraph object that use to draw the cnetplot will be saved to x and you can visualize it using other packages, for example networkD3 or RCytoscape, etc.

[EdS]

Thank you! I used the first of these methods, and it is exactly what I was looking for. Thanks for the help with this very useful tool!

Answer 2

[Max.Ka]

Hey Guangchuang Yu,

Sorry to revive this old question. I am now facing a similar issue with the function emapplot from the clusterProfiler package also wanting to load the results into cytoscape. Neither emapplot nor cnetplot do return an igraph object though. Instead a "list of 9" is returned. Would be great if there is a workaround.

Best Max

[wang.xu1990]

Hi, Did you succeed in load your result into Cytoscape? Could you tell me how you extracted the cnetplot or emapplot result and have a new visualizaiton?

Best,

Answer 3

[Hannes]

According to this post the cnetplot(fixed = F) is no longer supported in the recent clusterProfiler version. The doseplot package seems to be a workaround by using:

doseplot::cnetplot(x, fixed =T)

However in my case, doseplot is complaining that my compareCluster object is not supported as it gives me this error:

"unable to find an inherited method for function ‘cnetplot’ for signature ‘"compareClusterResult"’

I wonder if anyone else found a solution for this problem yet. If you are looking for exemplary data you can find them on zenodo.

[qiongfen0]

I also have the same problem, did you have any solutions now?