getIDEr {CIDER} | R Documentation |
Calculate the similarity matrix based on the metrics of Inter-group Differential ExpRession (IDER) with the selected batch effects regressed out.
getIDEr(
seu,
group.by.var = "initial_cluster",
batch.by.var = "Batch",
verbose = TRUE,
use.parallel = FALSE,
n.cores = 1,
downsampling.size = 40,
downsampling.include = TRUE,
downsampling.replace = TRUE
)
seu |
Seurat S4 object with the column of 'initial_cluster' in its meta.data. Required. |
group.by.var |
initial clusters (batch-specific groups) variable. Needs to be one of the 'colnames(seu@meta.data)'. Default: "initial_cluster". |
batch.by.var |
Batch variable. Needs to be one of the 'colnames(seu@meta.data)'. Default: "Batch". |
verbose |
Boolean. Print the message and progress bar. (Default: TRUE) |
use.parallel |
Boolean. Use parallel computation, which requires doParallel; no progress bar will be printed out. Run time will be 1/n.cores compared to the situation when no parallelisation is used. (Default: FALSE) |
n.cores |
Numeric. Number of cores used for parallel computing (default: 1). |
downsampling.size |
Numeric. The number of cells representing each group. (Default: 40) |
downsampling.include |
Boolean. Using 'include = TRUE' to include the group smaller than required size. (Default: FALSE) |
downsampling.replace |
Boolean. Using 'replace = TRUE' if the group is smaller than required size and some cells will be repeatedly used. (Default: FALSE) |
A list of four objects: a similarity matrix, a numeric vector recording cells used and the data frame of combinations included.
library(CIDER)
data("pancreas")
ider <- getIDEr(pancreas, downsampling.size = 30)
head(ider)