This repository has been archived by the owner on Jan 24, 2024. It is now read-only.
New aggregateNet of no-significant-pathway for netVisual_diffInteraction #688
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Dear Suoqin Jin,
When using aggregateNet() followed by netVisual_diffInteraction() for visualizing changes in cell-cell communication between two groups, it is possible only for pathways detected as overrepresented (with significant interaction) in both groups. Unfortunately, this is not always the case. In our research projects, we regularly find overrepresented pathways in only one of the disease conditions. In such cases, we still want to visualize and show the dimension of such differences.
I have introduced some slight modifications in three of your functions (aggregateNet, subsetCommunication, and subsetCommunication_internal) to calculate the aggregated network of nonsignificant pathways so they can be compared across groups. I created an example using your nonlesional (NL) and lesional (LS) data set for the TNF pathway, only detected as significant in the LS group (see zipped jupyter notebook in attachment, those lines changed are marked with #ADDED...).
It would be great if you could provide me feedback on such an approach, and if you are convinced, merge the changes included in the pull requests, so the community could also explore such functionality.
Best regards,
Alvaro
PS: I also added dplyr::summarize() in aggregateNet(). This solves an error when plyr is loaded after dplyr.
TEST_new_aggregateNet_netVisual_diffInteraction.zip