scDGE: Differential gene expression analysis for each cluster...

View source: R/scDGE.R

scDGER Documentation

Differential gene expression analysis for each cluster Perform differential analysis (DE) between two groups for each clusters

Description

Differential gene expression analysis for each cluster Perform differential analysis (DE) between two groups for each clusters

Usage

scDGE(
  object = object,
  comparison = c("condA", "condB"),
  group.by = NULL,
  min.cells = 20,
  min.pct = 0.1,
  logFC = 0.25,
  clusters = NULL
)

Arguments

object

Seurat object.

comparison

Vector of nominal variables from group.by. Eg., comparison=c('Normal', 'Tumor')

group.by

Regroup cells before performing DGE, default group.by='group'

min.cells

Minimum number of cells for DGE in any of the two groups, default min.cells=20

min.pct

Genes expressed in any of the two groups with a minium cell fraction (min.pct) are reserved for DGE, default min.pct=0.1

logFC

A positive value to set the cutoff of logFC, default logFC=0.25

clusters

Vector of clusters to perform DGE, default clusters=NULL, which means all clusters will be evaluated

Value

DGE Table

See Also

FindMarkers

Examples

data("H3N2_small")
x <- scDGE(object = H3N2_small, 
  comparison = c("Infected", "Bystander"),
  group.by = "group", 
  min.cells = 10, 
  logFC = 0.25, 
  clusters = NULL
)
head(x)


ncrna/Yeskit documentation built on Nov. 4, 2024, 10:32 p.m.