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I did a script with Seurat v5 to study TF activities in my 10X dataset. See below.
for (i in 1:length(r1.clustMats)) {
tfs <- CreateAssay5Object(r1.clustMats[[i]])
tfs <- NormalizeData(tfs)
tfs <- ScaleData(tfs, features = rownames(tfs))
TF.metacells[[i]] = viper(tfs@layers$scale.data, r1.net, minsize = 5)
}
r1.clustMats is a Large List, which contains 4 "matrix" "array". It's a scaled.data. I can access them with r1.clustMats[[1]] with genes for rownames and cells for colnames.
When I created an Assay with CreateAssay5Object, I lost the the rownames and the colnames. Then I can't run viper.
How to keep the rownames and the colnames when I create the assay?
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Dear Seurat community,
I did a script with Seurat v5 to study TF activities in my 10X dataset. See below.
r1.clustMats is a Large List, which contains 4 "matrix" "array". It's a scaled.data. I can access them with r1.clustMats[[1]] with genes for rownames and cells for colnames.
When I created an Assay with CreateAssay5Object, I lost the the rownames and the colnames. Then I can't run viper.
How to keep the rownames and the colnames when I create the assay?
Thank you for your help.
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