DESeqDataSet-class | R Documentation |
DESeqDataSet
is a subclass of RangedSummarizedExperiment
,
used to store the input values, intermediate calculations and results of an
analysis of differential expression. The DESeqDataSet
class
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
tximport package.
See the vignette for examples of construction from different types.
DESeqDataSet(se, design, ignoreRank = FALSE, skipIntegerMode = FALSE)
DESeqDataSetFromMatrix(
countData,
colData,
design,
tidy = FALSE,
ignoreRank = FALSE,
...
)
DESeqDataSetFromHTSeqCount(
sampleTable,
directory = ".",
design,
ignoreRank = FALSE,
...
)
DESeqDataSetFromTximport(txi, colData, design, ...)
se |
a |
design |
a |
ignoreRank |
use of this argument is reserved for DEXSeq developers only. Users will immediately encounter an error upon trying to estimate dispersion using a design with a model matrix which is not full rank. |
skipIntegerMode |
do not convert counts to integer mode (glmGamPoi allows non-integer counts) |
countData |
for matrix input: a matrix of non-negative integers |
colData |
for matrix input: a |
tidy |
for matrix input: whether the first column of countData is the rownames for the count matrix |
... |
arguments provided to |
sampleTable |
for htseq-count: a |
directory |
for htseq-count: the directory relative to which the filenames are specified. defaults to current directory |
txi |
for tximport: the simple list output of the |
Note on the error message "assay colnames() must be NULL or equal colData rownames()":
this means that the colnames of countData are different than the rownames of colData.
Fix this with: colnames(countData) <- NULL
A DESeqDataSet object.
See http://www-huber.embl.de/users/anders/HTSeq for htseq-count
countData <- matrix(1:100,ncol=4)
condition <- factor(c("A","A","B","B"))
dds <- DESeqDataSetFromMatrix(countData, DataFrame(condition), ~ condition)
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