plotCounts: Plot of normalized counts for a single gene

In mikelove/DESeq2: Differential gene expression analysis based on the negative binomial distribution

Plot of normalized counts for a single gene

Description

Normalized counts plus a pseudocount of 0.5 are shown by default.

Usage

plotCounts(
  dds,
  gene,
  intgroup = "condition",
  normalized = TRUE,
  transform = TRUE,
  main,
  xlab = "group",
  returnData = FALSE,
  replaced = FALSE,
  pc,
  ...
)

Arguments

dds	a DESeqDataSet
gene	a character, specifying the name of the gene to plot
intgroup	interesting groups: a character vector of names in colData(x) to use for grouping. Must be factor variables. If you want to plot counts over numeric, choose returnData=TRUE
normalized	whether the counts should be normalized by size factor (default is TRUE)
transform	whether to have log scale y-axis or not. defaults to TRUE
main	as in 'plot'
xlab	as in 'plot'
returnData	should the function only return the data.frame of counts and covariates for custom plotting (default is FALSE)
replaced	use the outlier-replaced counts if they exist
pc	pseudocount for log transform
...	arguments passed to plot

Examples

dds <- makeExampleDESeqDataSet()
plotCounts(dds, "gene1")

mikelove/DESeq2 documentation built on July 25, 2024, 11:11 p.m.