getContrast-method: Extract contrast matrix for linear mixed model

In variancePartition: Quantify and interpret divers of variation in multilevel gene expression experiments

Description

Extract contrast matrix, L, testing a single variable. Contrasts involving more than one variable can be constructed by modifying L directly

Usage

getContrast(exprObj, formula, data, coefficient)

Arguments

exprObj	matrix of expression data (g genes x n samples), or ExpressionSet, or EList returned by voom() from the limma package
formula	specifies variables for the linear (mixed) model. Must only specify covariates, since the rows of exprObj are automatically used a a response. e.g.: ~ a + b + (1|c) Formulas with only fixed effects also work
data	data.frame with columns corresponding to formula
coefficient	the coefficient to use in the hypothesis test

Value

Contrast matrix testing one variable

Examples

# load simulated data:
# geneExpr: matrix of gene expression values
# info: information/metadata about each sample
data(varPartData)

# get contrast matrix testing if the coefficient for Batch2 is zero 
# The variable of interest must be a fixed effect
form <- ~ Batch + (1|Individual) + (1|Tissue) 
L = getContrast( geneExpr, form, info, "Batch3")

# get contrast matrix testing if Batch3 - Batch2 = 0
form <- ~ Batch + (1|Individual) + (1|Tissue) 
L = getContrast( geneExpr, form, info, c("Batch3", "Batch2"))

# To test against Batch1 use the formula:
# 	~ 0 + Batch + (1|Individual) + (1|Tissue) 
# to estimate Batch1 directly instead of using it as the baseline

variancePartition documentation built on Nov. 8, 2020, 5:18 p.m.