#' Multidimensional Scaling
#'
#' Plot samples on principal coordinates.
#'
#' @param object A \code{matrix} or \code{RangedSummarizedExperiment} object.
#' @param group A factor specifying group colours.
#' @return A multidimensional scaling plot on the current graphics device.
plotMDS <- function(object, group) {
# Check argument missing
if (missing(object)) {
stop("`object` is missing, with no default.", call. = FALSE)
}
# Check argument class
if (!(class(object) %in% c("matrix", "RangedSummarizedExperiment"))) {
stop("`object` must be a matrix or RangedSummarizedExperiment class.", call. = FALSE)
}
# Dispatch method
UseMethod("plotMDS", object)
}
plotMDS.matrix <- function(object, group = NULL) {
# Retrieve assay matrix
assayMatrix <- object
# Remove ranges with zero variance
keepRowVars <- which(matrixStats::rowVars(assayMatrix) != 0)
assayMatrix <- assayMatrix[keepRowVars, ]
# Multidimensional scaling
assayDists <- dist(t(assayMatrix))
assayScale <- cmdscale(assayDists, eig = TRUE, k = 2)
# Define plotting data
sideValues1 <- assayScale$points[, 1]
sideValues2 <- assayScale$points[, 2]
# Define pretty breaks
sideBreaks1 <- pretty(sideValues1)
sideBreaks2 <- pretty(sideValues2)
# Define pretty limits
sideLimits1 <- range(sideBreaks1)
sideLimits2 <- range(sideBreaks2)
# Create colour palette
colorPalette <- RColorBrewer::brewer.pal(n = 3, name = "Dark2")
# Define colours by group
if (is.null(group)) {
groupFactor <- as.factor(seq_len(ncol(object)))
groupColors <- rep(colorPalette, length.out = length(groupFactor))
} else {
groupFactor <- as.factor(group)
groupColors <- colorPalette[as.integer(groupFactor)]
}
# Draw plotting area
plot(x = sideValues1,
y = sideValues2,
pch = 21,
cex = 2,
bg = groupColors,
main = "Classical multidimensional scaling",
xlab = "Coordinate 1",
ylab = "Coordinate 2",
xlim = sideLimits1,
ylim = sideLimits2,
xaxt = "n",
yaxt = "n")
# Draw axis ticks
axis(side = 1, at = sideBreaks1, las = 0)
axis(side = 2, at = sideBreaks2, las = 2)
# Draw plot legend
legend("topleft",
legend = levels(groupFactor),
pch = 21,
cex = 1,
pt.bg = unique(groupColors),
bty = "n")
}
plotMDS.RangedSummarizedExperiment <- function(object, group = NULL) {
# Filter by size and methylation
sizeFilter <- mcols(object)$filterBySize
exprFilter <- mcols(object)$filterByExpr
# Retrieve assay matrix
if (is.null(sizeFilter) | is.null(exprFilter)) {
assayMatrix <- assay(object, "qsmoothData")
} else {
assayFilter <- sizeFilter & exprFilter
assayMatrix <- assay(object, "qsmoothData")[assayFilter, ]
}
# Multidimensional scaling
assayDists <- dist(t(assayMatrix))
assayScale <- cmdscale(assayDists, eig = TRUE, k = 2)
# Define plotting data
sideValues1 <- assayScale$points[, 1]
sideValues2 <- assayScale$points[, 2]
# Define pretty breaks
sideBreaks1 <- pretty(sideValues1)
sideBreaks2 <- pretty(sideValues2)
# Define pretty limits
sideLimits1 <- range(sideBreaks1)
sideLimits2 <- range(sideBreaks2)
# Create colour palette
colorPalette <- RColorBrewer::brewer.pal(n = 3, name = "Dark2")
# Define colours by group
if (is.null(group)) {
groupFactor <- as.factor(seq_len(ncol(object)))
groupColors <- rep(colorPalette, length.out = length(groupFactor))
} else {
groupFactor <- as.factor(group)
groupColors <- colorPalette[as.integer(groupFactor)]
}
# Draw plotting area
plot(x = sideValues1,
y = sideValues2,
pch = 21,
cex = 2,
bg = groupColors,
main = "Multidimensional scaling",
xlab = "Coordinate 1",
ylab = "Coordinate 2",
xlim = sideLimits1,
ylim = sideLimits2,
xaxt = "n",
yaxt = "n")
# Draw axis ticks
axis(side = 1, at = sideBreaks1, las = 0)
axis(side = 2, at = sideBreaks2, las = 2)
# Draw plot legend
legend("topleft",
legend = levels(groupFactor),
pch = 21,
cex = 1,
pt.bg = unique(groupColors),
bty = "n")
}
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