How to extract the names of genes that suffer a loss in number of interactions in the comparison of two datasets?

[MANZHAOHUI]

Hi, I've created two cellchat objects, AD (alzheimer's) with MDD (Major depression disorder) vs. Normal and AD without MDD vs. Normal based on scRNAseq data. Then I merged them using object.list <- list(LOAD.WITH.DEP=cellchat1,LOAD.WITHOUT.DEP=cellchat2) cellchat <- mergeCellChat(object.list,add.names = names(object.list))

Then, I can visualize the change of number of cell cell interactions between the two datasets by using: netVisual_diffInteraction(cellchat, vertex.label.cex = 2.5, weight.scale = T,comparison = c("LOAD.WITH.DEP","LOAD.WITHOUT.DEP"))

However, how can I extract the genes that suffer a loss of cell cell interactions in this comparison?

Thank you.

[sqjin]

@MANZHAOHUI Please check our tutorial. You may find useful information in ". Identify cell populations with significant changes in sending or receiving signals between different datasets by following option A, or identify the signaling changes of specific cell populations by following option B. "