plotCorrStructure

Plot correlation structure of a gene based on random effects

Usage

plotCorrStructure(
  fit,
  varNames = names(coef(fit)),
  reorder = TRUE,
  pal = colorRampPalette(c("white", "red", "darkred")),
  hclust.method = "complete"
)

Arguments

fit

linear mixed model fit of a gene produced by lmer() or fitVarPartModel()

varNames

variables in the metadata for which the correlation structure should be shown. Variables must be random effects

reorder

how to reorder the rows/columns of the correlation matrix. reorder=FALSE gives no reorder. reorder=TRUE reorders based on hclust. reorder can also be an array of indices to reorder the samples manually

pal

color palette

hclust.method

clustering methods for hclust

Value

Image of correlation structure between each pair of experiments for a single gene

Examples

# load library
# library(variancePartition)

library(BiocParallel)

# load simulated data:
data(varPartData)

# specify formula
form <- ~ Age + (1 | Individual) + (1 | Tissue)

# fit and return linear mixed models for each gene
fitList <- fitVarPartModel(geneExpr[1:10, ], form, info)

# Focus on the first gene
fit <- fitList[[1]]

# plot correlation sturcture based on Individual, reordering samples with hclust
plotCorrStructure(fit, "Individual")


# don't reorder
plotCorrStructure(fit, "Individual", reorder = FALSE)


# plot correlation sturcture based on Tissue, reordering samples with hclust
plotCorrStructure(fit, "Tissue")


# don't reorder
plotCorrStructure(fit, "Tissue", FALSE)


# plot correlation structure based on all random effects
# reorder manually by Tissue and Individual
idx <- order(info$Tissue, info$Individual)
plotCorrStructure(fit, reorder = idx)


# plot correlation structure based on all random effects
# reorder manually by Individual, then Tissue
idx <- order(info$Individual, info$Tissue)
plotCorrStructure(fit, reorder = idx)