smorabit
commented
2 months ago Hi,
I want to ask whether this is possible with the implementation in hdWGCNA?
This is not possible with hdWGCNA directly (unless you format your bulk data as a Seurat object), since this package is not built to be used with bulk transcriptomic datasets. Fortunately the original WGCNA package is built for bulk datasets and you should be able to use it. I can provide some code which may help but you will probably need to make some modifications for your particular data.
You are going to want to look at this function from WGCNA, and you will need to supply it with your two expression matrices and the set of gene modules. You can get the expression matrix from the hdWGCNA metacells like this:
datExpr <- GetDatExpr(seurat_obj)Importantly, you need to make sure that the genes in the bulk RNA dataset match the single-cell dataset.
# suppose you have a samples x genes bulk RNAseq dataset called bulk_df
head(bulk_df)
# get the genes that are in common:
genes_bulk <- colnames(bulk_df)
genes_sc <- colnames(datExpr)
genes_keep <- genes_bulk[genes_bulk %in% genes_sc]
bulk_df <- bulk_df[,genes_keep]
Next set up both expression matrices for the modulePreservation WGCNA function.
# set up multiExpr:
setLabels <- c("ref", "query")
multiExpr <- list(
ref = list(data=datExpr_ref),
query = list(data=datExpr_query)
)
# set up the modules
ref_modules <- list(ref = GetModules(seurat_obj)$module)
Run the modulePreservation function
mp <- WGCNA::modulePreservation(
multiExpr,
ref_modules,
referenceNetworks = 1,
nPermutations = 100 # set this to whatever number is suitable for you
)Note that I did not run this code and I am not sure if it will work, but I hope that it will help you get started!
zitiansunshine
Dear Sam,
Hi, thank you very much for developing this amazing tool. I identified modules from a single cell RNA-seq dataset, and I am interested in checking whether the module is preserved in a bulk RNA-seq dataset from the same tissue. I want to ask whether this is possible with the implementation in hdWGCNA? Thank you very much.