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Perform Hierarchical Clustering

Source: R/Examine_Region_Methylation.R
getDendro.Rd

getDendro() computes the distance between the rows of a matrix and performs hierarchical clustering. Possible distance measures include euclidean, pearson, and bicor. The function also optionally transposes the matrix.

Usage

getDendro(
  x,
  transpose = FALSE,
  distance = c("euclidean", "pearson", "bicor"),
  maxPOutliers = 0.1,
  verbose = TRUE
)

Arguments

x

A numeric matrix.

transpose

A logical(1) specifying whether to transpose the matrix.

distance

A character(1) indicating which distance measure to use. Possible values include euclidean, pearson, and bicor.

maxPOutliers

A numeric(1) specifying the maximum percentile that can be considered outliers on each side of the median for the bicor statistic.

verbose

A logical(1) indicating whether messages should be printed.

Value

An stats::hclust object that describes the clustering tree.

Details

Euclidean distance is calculated by stats::dist(), where method = "euclidean", while Pearson correlation and biweight midcorrelation (bicor) are computed by WGCNA::cor() and WGCNA::bicor(), respectively. The cor and bicor are then subtracted from 1 to calculate the dissimilarity. Hierarchical clustering is done by stats::hclust(), where method = "average".

See also

Examples

if (FALSE) {

# Assess Sample Similarity
getDendro(methAdj, distance = "euclidean") %>%
        plotDendro(file = "Sample_Dendrogram.pdf", expandY = c(0.25,0.08))

# Examine Correlations between Modules
moduleDendro <- getDendro(MEs, distance = "bicor")
plotDendro(moduleDendro, labelSize = 4, nBreaks = 5,
           file = "Module_ME_Dendrogram.pdf")

# Characterize Correlations between Samples
sampleDendro <- getDendro(MEs, transpose = TRUE, distance = "bicor")
plotDendro(sampleDendro, labelSize = 3, nBreaks = 5,
           file = "Sample_ME_Dendrogram.pdf")

# Examine Correlations between Traits
traitDendro <- getCor(MEs, y = colData, corType = "bicor",
                      robustY = FALSE) %>%
        getDendro(transpose = TRUE)
plotDendro(traitDendro, labelSize = 3.5, expandY = c(0.65,0.08),
           file = "Trait_Dendrogram.pdf")
}