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rezakj / iCellR

Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).
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Possible to cluster based on ADT data alone? #4

Closed cpcook1 closed 4 years ago

cpcook1 commented 4 years ago

Hi I was wondering if it is possible to cluster on the ADT data alone, and if so, how to go about it? When I try using Seurat and PCA I get a warning message "The object only has information for 25 reductions" since we have only run 25 Abs, and subsequently we only get 1-2 PC's.

If I try using creating a distance matrix as per the seurat vignette the object is too large and the computer will not accept it. Is it possible in iCellR?

rezakj commented 4 years ago

Yes, it's possible to cluster based on ADTs. Here is how it works:

1- get you ADT names from the main data slot:

grep("^ADT_", rownames(my.obj@main.data),value=T)
# [1] "ADT_CD3"    "ADT_CD4"    "ADT_CD8"    "ADT_CD45RA" "ADT_CD56"
# [6] "ADT_CD16"   "ADT_CD11c"  "ADT_CD14"   "ADT_CD19"   "ADT_CD34"

MyADTS <- grep("^ADT_", rownames(my.obj@main.data),value=T)

2- Run PCA based on ADTs and all is good. Because, tSNE and UMAP will be running based on PCA the rest of your analysis will be based on ADTs.

my.obj <- run.pca(my.obj, method = "gene.model", gene.list = MyADTS, data.type = "main")