differential_Seurat: Differential function Seurat (wilcoxon)

In vallotlab/IDclust: Iterative Differential Clustering for single-cell

Differential function Seurat (wilcoxon)

Description

Run Seurat::FindAllMarkers() function on the clusters in the 'by' column and return a data.frame containing the marker genes of each cluster passing the thresholds .

Usage

differential_Seurat(
  object,
  by = "IDcluster",
  logFC.th = log2(1.5),
  qval.th = 0.01,
  min.pct = 0.1,
  ...
)

Arguments

object	A Seurat object containing scRNA dataset with a metadata column name matching the by parameter
by	A character specifying the name of the metadata column referencing the clusters.
logFC.th	A numeric specifying the log2 fold change of activation above/below which a feature is considered as significantly differential.
qval.th	A numeric specifying the adjusted p-value below which a feature is considered as significantly differential.
min.pct	Minimum percentage of cells to be active in the cells of the cluster to consider a feature as potentially significantly differential.
...	Additional parameters to pass to Seurat::FindAllMarkers().

See Also

See Seurat::FindAllMarkers()

Examples

if(requireNamespace("Seurat", quietly=TRUE)){
data("Seu", package = "IDclust")
DA <- differential_Seurat(Seu)
}

vallotlab/IDclust documentation built on Feb. 16, 2023, 8:58 a.m.