No signaling genes when using mergeCellChat()

[learning-MD]

Hi,

I've got a scRNA-seq dataset with 2 different conditions. I've split them into separate Seurat objects and made cellchat objects with them individually. I can run through the single-condition cellchat vignettes without issue (https://htmlpreview.github.io/?https://github.com/sqjin/CellChat/blob/master/tutorial/CellChat-vignette.html). However, whenever I merge them together, I get 0 signaling genes for the 43,000 cells. I've followed the typical workflow from the tutorial:

For each individual condition:
data.input <- GetAssayData(seurat_object, assay = "SCT", slot = "data")
labels <- Idents(seurat_object)
meta <- data.frame(group = labels, row.names = names(labels))
cellchat <- createCellChat(object = data.input, meta = meta, group.by = "labels")

Merging the the 2 conditions:
object.list <- list(disease = cellchat.disease, control = cellchat.control)
cellchat <- mergeCellChat(object.list, add.names = names(object.list))

I've tried other methods to make the cellchat objects as well:

cellchat_disease <- createCellChat(seurat_object, group.by = "meta.data_column")

And merged the conditions that way. I still get 0 signaling genes in the merged output. Additionally, if I look at [email protected] (for example), the result is a <0 x 0 matrix..

I'm using Seurat version 4.0.3 if that helps. Any advice would be much appreciated. Thanks!

[flde]

I had the same problem but when adding the CellChatDB and run subsetData() on the individual samples first it works e.g. there are genes in the [email protected] slot. However, to use the full merged data workflow I also need to run the other computations including aggregateNet() on the individual data sets before merging.

Makes sense and in the comparison vignette it also states "USERS need to run CellChat on each dataset seperately and then merge different CellChat objects together.". Its just a bit confusing which steps that includes.