Description Usage Arguments Details Value Author(s)
View source: R/GEX_process_dds.R
Process count matrix of DESeqDataSet and optionally convert it to a SummarizedExperiment object.
1 2 3 4 5 6 7 8 | process_dds(
dds,
min_rowsum = 10,
norm_sizeFactors = FALSE,
transform.function = NULL,
return_SummarizedExperiment = FALSE,
...
)
|
dds |
|
min_rowsum |
numeric. Minimum rowsum of countmatrix. All rows with |
norm_sizeFactors |
logical. If |
transform.function |
function name to be used for data transformation,
e.g. |
return_SummarizedExperiment |
logical. If |
... |
further parameter for |
The count matrix of the input object is filtered for low abundancy transcripts, normalized for
library size factor (size factors are first calculated if necessary) and is transformed
according to the function given in transform.function
. Parameters for the selected
transform.function
can be passed via the ...
-argument (see help for the
respective function). The DESeq2
package recommends varianceStabilizingTransformation
for further processing of the read count matrix. If you prefer to analyse reads with limma, you may
apply voom
transformation as recommended in the limma
documentation. The voom
transformation can be complemented by the same between-array normalization methods as would be used
for microarrays (e.g. quantile normalization) via the normalize.method
parameter of voom
.
The function will return either the processed input object or an SummarizedExperiment
object
if return_SummarizedExperiment
is set to TRUE
. In this case, the design parameter of
the initial DESeqDataSet
is omitted.
SummarizedExperiment
or processed input object (matrix
, DESeqDataSet
or
DESeqTransform
depending on applied data transformation)
Frank Ruehle
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