(counts=exp_mat.1,min.cells=3,min.features=50)query.list[["protector"]]$Sample<-substring(colnames(query.list[["protector"]]),18)query.list[["protector"]]$condition<-"protector"query.list[["control"]]<-CreateSeuratObject(counts=exp_mat.2,min.cells=3,min.features=50)query.list[["cont...
For analyzing datasets composed of multiple batches (e.g. different subjects, technologies), we recommend projecting each batch separately, by providing ProjecTILs a list of Seurat objects as input, e.g.: data.seurat.list<-SplitObject(data.seurat,split.by="batch")query.projected.list<-make.pr...
[19] S4Vectors_0.20.1 BiocGenerics_0.28.0 loaded via a namespace (and not attached): [1] Seurat_3.2.0 Rtsne_0.15 colorspace_1.4-1 deldir_0.1-28 ggridges_0.5.1 rstudioapi_0.9.0 spatstat.data_1.4-3 [8] leiden_0.3.1 listenv_0.7.0 npsurv_0.4-0 ggrepel_0.8.0 codetools_0.2-16 ...
wget -O myo_slim_seurat_v1-1.RData https://datadryad.org/stash/downloads/file_stream/1113823 CellChat object: wget -O scMuscle_cellchat_v1-1.RData https://datadryad.org/stash/downloads/file_stream/1113826 Preprocessed Visium data: wget -O vis_slim_v1.RData https://datadryad....