splitOn | R Documentation |
TreeSummarizedExperiment
column-wise or row-wise based on grouping variableSplit TreeSummarizedExperiment
column-wise or row-wise based on grouping variable
splitOn(x, ...)
## S4 method for signature 'SummarizedExperiment'
splitOn(x, f = NULL, ...)
## S4 method for signature 'SingleCellExperiment'
splitOn(x, f = NULL, ...)
## S4 method for signature 'TreeSummarizedExperiment'
splitOn(x, f = NULL, update.tree = update_rowTree, update_rowTree = FALSE, ...)
unsplitOn(x, ...)
## S4 method for signature 'list'
unsplitOn(x, update.tree = update_rowTree, update_rowTree = FALSE, ...)
## S4 method for signature 'SimpleList'
unsplitOn(x, update.tree = update_rowTree, update_rowTree = FALSE, ...)
## S4 method for signature 'SingleCellExperiment'
unsplitOn(
x,
altexp = altExpNames,
altExpNames = names(altExps(x)),
keep.dimred = keep_reducedDims,
keep_reducedDims = FALSE,
...
)
x |
|
... |
Arguments passed to
|
f |
|
update.tree |
|
update_rowTree |
Deprecated. Use |
altexp |
|
altExpNames |
Deprecated. Use |
keep.dimred |
|
keep_reducedDims |
Deprecated. Use |
splitOn
split data based on grouping variable. Splitting can be done
column-wise or row-wise. The returned value is a list of
SummarizedExperiment
objects; each element containing members of each
group.
For splitOn
: SummarizedExperiment
objects in a SimpleList
.
For unsplitOn
: x
, with rowData
and assay
data replaced by the unsplit data. colData
of x is kept as well
and any existing rowTree
is dropped as well, since existing
rowLinks
are not valid anymore.
Leo Lahti and Tuomas Borman. Contact: microbiome.github.io
agglomerateByRanks
agglomerateByVariable
,
sumCountsAcrossFeatures
,
agglomerateByRank
,
altExps
,
splitAltExps
data(GlobalPatterns)
tse <- GlobalPatterns
# Split data based on SampleType.
se_list <- splitOn(tse, f = "SampleType")
# List of SE objects is returned.
se_list
# Create arbitrary groups
rowData(tse)$group <- sample(1:3, nrow(tse), replace = TRUE)
colData(tse)$group <- sample(1:3, ncol(tse), replace = TRUE)
# Split based on rows
# Each element is named based on their group name. If you don't want to name
# elements, use use_name = FALSE. Since "group" can be found from rowdata and colData
# you must use `by`.
se_list <- splitOn(tse, f = "group", use.names = FALSE, by = 1)
# When column names are shared between elements, you can store the list to altExps
altExps(tse) <- se_list
altExps(tse)
# If you want to split on columns and update rowTree, you can do
se_list <- splitOn(tse, f = colData(tse)$group, update.tree = TRUE)
# If you want to combine groups back together, you can use unsplitBy
unsplitOn(se_list)
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