plotBaseMean: Plot base mean distribution

In steinbaugh/DESeqAnalysis: Acid Genomics DESeq2 Analysis Utilities

Plot base mean distribution

Description

The base mean is the mean of normalized counts of all samples, normalizing for sequencing depth.

Usage

plotBaseMean(object, ...)

## S4 method for signature 'DESeqAnalysis'
plotBaseMean(
  object,
  nonzero = TRUE,
  trans = c("log10", "log2", "identity"),
  summary = TRUE,
  labels = list(title = "Base mean distribution", subtitle = NULL)
)

## S4 method for signature 'DESeqDataSet'
plotBaseMean(
  object,
  nonzero = TRUE,
  trans = c("log10", "log2", "identity"),
  summary = TRUE,
  labels = list(title = "Base mean distribution", subtitle = NULL)
)

## S4 method for signature 'DESeqResults'
plotBaseMean(
  object,
  nonzero = TRUE,
  trans = c("log10", "log2", "identity"),
  summary = TRUE,
  labels = list(title = "Base mean distribution", subtitle = NULL)
)

Arguments

object	Object.
nonzero	logical(1). Remove zero-count features (genes).
trans	character(1). Name of the axis scale transformation to apply. For more information: help(topic = "scale_x_continuous", package = "ggplot2")
summary	logical(1). Include distribution summary statistics as lines on the plot.
labels	list. ggplot2 labels. See ggplot2::labs() for details.
...	Additional arguments.

Value

ggplot.

Functions

• plotBaseMean(DESeqAnalysis): Passes to DESeqDataSet method.

• plotBaseMean(DESeqDataSet): Generates row means of normalized counts. This value corresponds to the baseMean column of DESeqResults.

• plotBaseMean(DESeqResults): Uses baseMean column of results.

Note

Updated 2022-05-17.

See Also

• https://support.bioconductor.org/p/75244/

• summary().

Examples

data(deseq)

## DESeqAnalysis ====
plotBaseMean(deseq)

steinbaugh/DESeqAnalysis documentation built on Oct. 13, 2023, 5:39 a.m.