Plot MDS from normalized count data

Uses cmdscale to get multidimensional scaling of data matrix, and plot the samples with ggplot2.

degMDS(counts, condition = NULL, k = 2, d = "euclidian", xi = 1,
  yi = 2)

Arguments

counts	matrix samples in columns, features in rows
condition	vector define groups of samples in counts. It has to be same order than the count matrix for columns.
k	integer number of dimensions to get
d	type of distance to use, c("euclidian", "cor").
xi	number of component to plot in x-axis
yi	number of component to plot in y-axis

Value

ggplot2 object

Examples

data(humanGender)
library(DESeq2)
idx <- c(1:10, 75:85)
dse <- DESeqDataSetFromMatrix(assays(humanGender)[[1]][1:1000, idx],
  colData(humanGender)[idx,], design=~group)
degMDS(counts(dse), condition = colData(dse)[["group"]])