View source: R/differential_abundance.R
findDiffAbundantCells | R Documentation |
This function warp Steps 1~3 of DAseq algorithm from
package getDAcells
findDiffAbundantCells( obj, ctrl, stim, reduction = "pca", npc = 20, pred.thres = NULL, k.vector = NULL, resolution = 0.05 )
obj |
Seurat object |
ctrl |
Control condition |
stim |
Stimulus condition |
reduction |
Which dimensionality reduction to use |
npc |
How many dimensions to use as input features |
pred.thres |
length-2 vector, top and bottom threshold on DA measure, default NULL, select significant DA cells based on permutation |
k.vector |
vector, k values to create the score vector |
resolution |
parameter for Seurat function FindClusters(), default 0.05 |
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