DESeqDataSet is a subclass of
used to store the input values, intermediate calculations and results of an
analysis of differential expression. The
enforces non-negative integer values in the "counts" matrix stored as
the first element in the assay list.
In addition, a formula which specifies the design of the experiment must be provided.
The constructor functions create a DESeqDataSet object
from various types of input:
a RangedSummarizedExperiment, a matrix, count files generated by
the python package HTSeq, or a list from the tximport function in the
See the vignette for examples of construction from different types.
DESeqDataSet(se, design, ignoreRank = FALSE)
DESeqDataSetFromMatrix(countData, colData, design, tidy = FALSE, ignoreRank = FALSE, ...)
DESeqDataSetFromHTSeqCount(sampleTable, directory = ".", design, ignoreRank = FALSE, ...)
DESeqDataSetFromTximport(txi, colData, design, ...)
RangedSummarizedExperiment with columns of variables
indicating sample information in
and the counts as the first element in the assays list, which will
be renamed "counts". A
RangedSummarizedExperiment object can be
generated by the function
summarizeOverlaps in the GenomicAlignments
formula which expresses how the counts for each gene
depend on the variables in
colData. Many R
formula are valid,
including designs with multiple variables, e.g.,
~ group + condition,
and designs with interactions, e.g.,
~ genotype + treatment + genotype:treatment.
results for a variety of designs and how to extract results tables.
By default, the functions in this package will use
the last variable in the formula for building results tables and plotting.
~ 1 can be used for no design, although users need to remember
to switch to another design for differential testing.
data.frame with at least a single column.
Rows of colData correspond to columns of countData
SummarizedExperiment including rowRanges and metadata. Note that
for Bioconductor 3.1, rowRanges must be a GRanges or GRangesList, with potential metadata columns
as a DataFrame accessed and stored with
mcols. If a user wants to store metadata columns
about the rows of the countData, but does not have GRanges or GRangesList information,
first construct the DESeqDataSet without rowRanges and then add the DataFrame with
data.frame with three or more columns. Each row
describes one sample. The first column is the sample name, the second column
the file name of the count file generated by htseq-count, and the remaining
columns are sample metadata which will be stored in
colnames(countData) <- NULL