Construct a new SummarizedExperiment by splitting one of the assays
into a list of assays, each of which contains features of a given
'type'. It is assumed that there is a one-to-one correspondence
between feature sets of different types; for example, these can be
spliced and unspliced variants of the same transcripts. The type of
each feature in the original SummarizedExperiment, and the correspondence
between the features of different types, are given in a data.frame.
splitSE(se, splitDf, assayName)A SummarizedExperiment object.
A data.frame with feature IDs. Each column
represents a separate feature type, and the features in a given
row are considered representatives of the same feature (and will
be represented as one feature in the output object).
A character scalar, indicating the assay of se
that will be split. Must be one of assayNames(se).
A SummarizedExperiment object with the same columns
as the input object, and the same number of assays as the number
of columns in splitDf. The assays will be named by the
column names of splitDf. The colData and metadata
of the input SummarizedExperiment object are copied to the
output object. The row names are set to the feature IDs in the
first column of splitDf.
se <- SummarizedExperiment::SummarizedExperiment(
assays = S4Vectors::SimpleList(
counts = as(matrix(1:15, nrow = 5), "sparseMatrix"),
logcounts = log2(matrix(1:15, nrow = 5))
),
colData = S4Vectors::DataFrame(sID = paste0("S", 1:3),
condition = c("A", "A", "B")),
metadata = list(md1 = "annotation")
)
rownames(se) <- paste0("G", 1:5)
colnames(se) <- paste0("P", 1:3)
splitDf <- data.frame(spliced = c("G1", "G2", "G6"),
unspliced = c("G3", "G5", "G4"),
stringsAsFactors = FALSE)
splse <- splitSE(se = se, splitDf = splitDf, assayName = "counts")