limmaDE: Simple differential expression with limma

In bartongroup/Proteus: Downstream analysis of the MaxQuant output

Simple differential expression with limma

Description

limmaDE is a wrapper around limma to perform a differential expression between a pair of conditions.

Usage

limmaDE(
  pdat,
  formula = "~condition",
  conditions = NULL,
  transform.fun = log2,
  sig.level = 0.05
)

Arguments

pdat	Protein proteusData object.
formula	A string with a formula for building the linear model.
conditions	A character vector with two conditions for differential expression. Can be omitted if there are only two condition in pdat.
transform.fun	A function to transform data before differential expression.
sig.level	Significance level for rejecting the null hypothesis.

Details

Before limma is called, intensity data are transformed using the transform.fun function. The default for this transformation is log2. Therefore, by default, the column "logFC" in the output data frame contains log2 fold change. If you need log10-based fold change, you can use transform.fun=log10.

limmaDE is only a simple wrapper around limma, to perform differential expression between two conditions. For more complicated designs we recommend using limma functions directly.

Value

A data frame with DE results. "logFC" column is a log-fold-change (using the transform.fun). Two columns with mean log-intensity (again, using transform.fun) and two columns with the number of good replicates (per condition) are added. Attributes contain additional information about the transformation function, significance level, formula and conditions.

Examples

library(proteusLabelFree)
data(proteusLabelFree)
prodat.med <- normalizeData(prodat)
res <- limmaDE(prodat.med)

bartongroup/Proteus documentation built on April 22, 2023, 5:33 a.m.