Clean the SummarizedExperiment by making sure that names of various fields are available and unique.
cleanDataset(se)
# S4 method for SummarizedExperiment
cleanDataset(se)
# S4 method for SingleCellExperiment
cleanDataset(se)A SummarizedExperiment object or one of its subclasses.
A cleaned version of se.
Various Panels assume that the row and column names of the input SummarizedExperiment are available and unique.
This function enforces that, adding consecutive integer names if not available and calling make.unique if they are duplicated.
Various Panels further assume that the assay, rowData, colData names are unique;
if this is not the case, selectInput behaves in unexpected (and incorrect) ways.
This function enforces that as well by running them through make.unique.
For SingleCellExperiment object, we enforce uniqueness in the reducedDims.
All changes result in warnings as a “sensible” object is not expected to require any work.
# Creating a very naughty SE.
se <- SummarizedExperiment(list(cbind(1:10, 2:11), cbind(2:11, 3:12)),
colData=DataFrame(A=1:2, A=3:4, check.names=FALSE),
rowData=DataFrame(B=1:10, B=1:10, check.names=FALSE))
se
#> class: SummarizedExperiment
#> dim: 10 2
#> metadata(0):
#> assays(2): '' ''
#> rownames: NULL
#> rowData names(2): B B
#> colnames: NULL
#> colData names(2): A A
cleanDataset(se)
#> Warning: filling in the missing 'rownames(se)'
#> Warning: filling in the missing 'colnames(se)'
#> Warning: duplicated 'colnames(rowData(se))' detected, making them unique
#> Warning: duplicated 'colnames(colData(se))' detected, making them unique
#> Warning: empty 'assayNames(se)' detected, renaming to 'unnamed'
#> Warning: duplicated 'assayNames(se)' detected, making them unique
#> class: SummarizedExperiment
#> dim: 10 2
#> metadata(0):
#> assays(2): unnamed unnamed.1
#> rownames(10): 1 2 ... 9 10
#> rowData names(2): B B.1
#> colnames(2): 1 2
#> colData names(2): A A.1