splitSE: Split SummarizedExperiment by gene categories
In tximeta: Transcript Quantification Import with Automatic Metadata

Description Usage Arguments Value Examples

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.

1	splitSE(se, splitDf, assayName)

`se`	A `SummarizedExperiment` object.
`splitDf`	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).
`assayName`	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")