plotCorrStructure {variancePartition} | R Documentation

## plotCorrStructure

### Description

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)

    # 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:
    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 )

    # stop cluster
    stopCluster(cl)

[Package variancePartition version 1.12.3 Index]