variancePartition (version 1.2.5)

getVarianceComponents: Extract variance terms

Description

Extract variance terms from a model fit with lm() or lmer()

Usage

getVarianceComponents(fit)

Arguments

fit

list of lmer() model fits

Value

variance explained by each variable

Examples

# library(variancePartition)

# optional step to run analysis in parallel on multicore machines
# Here, we used 4 threads
library(doParallel)
cl <- makeCluster(4)
registerDoParallel(cl)
# or by using the doSNOW package

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

# Specify variables to consider
# Age is continuous so we model it as a fixed effect
# Individual and Tissue are both categorical, so we model them as random effects
form <- ~ Age + (1|Individual) + (1|Tissue) 

# Fit model and extract variance in two separate steps
# Step 1: fit model for each gene, store model fit for each gene in a list
modelList <- fitVarPartModel( geneExpr, form, info )

fit <- modelList[[1]]
getVarianceComponents( fit )

# stop cluster
stopCluster(cl)