DGEList: DGEList Constructor
In edgeR: Empirical Analysis of Digital Gene Expression Data in R

Description Usage Arguments Details Value Author(s) See Also Examples

Creates a DGEList object from a table of counts (rows=features, columns=samples), group indicator for each column, library size (optional) and a table of feature annotation (optional).

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DGEList(counts = matrix(0, 0, 0), lib.size = colSums(counts),
        norm.factors = rep(1,ncol(counts)), samples = NULL,
        group = NULL, genes = NULL, remove.zeros = FALSE)

`counts`	numeric matrix of read counts.
`lib.size`	numeric vector giving the total count (sequence depth) for each library.
`norm.factors`	numeric vector of normalization factors that modify the library sizes.
`samples`	data frame containing information for each sample.
`group`	vector or factor giving the experimental group/condition for each sample/library.
`genes`	data frame containing annotation information for each gene.
`remove.zeros`	logical, whether to remove rows that have 0 total count.

To facilitate programming pipelines, NULL values can be input for lib.size, norm.factors, samples or group, in which case the default value is used as if the argument had been missing.

a DGEList object

edgeR team. First created by Mark Robinson.

DGEList-class

ngenes <- 1000
nsamples <- 4
Counts <- matrix(rnbinom(ngenes*nsamples,mu=5,size=2),ngenes,nsamples)
rownames(Counts) <- 1:ngenes
y <- DGEList(counts=Counts, group=rep(1:2,each=2))
dim(y)
colnames(y)
y$samples
y$genes <- data.frame(Symbol=paste0("Gene",1:ngenes))
show(y)

Loading required package: limma
[1] 1000    4
[1] "Sample1" "Sample2" "Sample3" "Sample4"
        group lib.size norm.factors
Sample1     1     5180            1
Sample2     1     4977            1
Sample3     2     5220            1
Sample4     2     4912            1
An object of class "DGEList"
$counts
  Sample1 Sample2 Sample3 Sample4
1       1       6       0       2
2       4      10       6       1
3       7       6       2       4
4       5       8       0      13
5       3       4       3       7
995 more rows ...

$samples
        group lib.size norm.factors
Sample1     1     5180            1
Sample2     1     4977            1
Sample3     2     5220            1
Sample4     2     4912            1

$genes
  Symbol
1  Gene1
2  Gene2
3  Gene3
4  Gene4
5  Gene5
995 more rows ...