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)
matrix samples in columns, features in rows
vector define groups of samples in counts. It has to be same order than the count matrix for columns.
integer number of dimensions to get
type of distance to use, c("euclidian", "cor").
number of component to plot in x-axis
number of component to plot in y-axis
data(humanGender) library(DESeq2) idx <- c(1:10, 75:85) dse <- DESeqDataSetFromMatrix(assays(humanGender)[][1:1000, idx], colData(humanGender)[idx,], design=~group) degMDS(counts(dse), condition = colData(dse)[["group"]])