degMDS {DEGreport} | R Documentation

## Plot MDS from normalized count data

### Description

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

### Usage

    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"]])

[Package DEGreport version 1.16.0 Index]