treeSummarizedExperiment-accessor: Accessor functions for treeSummarizedExperiment
In markrobinsonuzh/treeAGG: Tree Aggregation

Description Usage Arguments Value Author(s) See Also Examples

Accessor functions to extract different elements from treeSummarizedExperiment object.

## S4 method for signature 'treeSummarizedExperiment'
assays(x, use.nodeLab = FALSE, ...,
  withDimnames = FALSE)

## S4 method for signature 'treeSummarizedExperiment'
rowData(x, use.names = TRUE, ...)

linkData(x)

## S4 method for signature 'treeSummarizedExperiment'
linkData(x)

treeData(x)

## S4 method for signature 'treeSummarizedExperiment'
treeData(x)

## S4 method for signature 'treeSummarizedExperiment,ANY,ANY,ANY'
x[i, j]

getByLink(x, subset)

## S4 method for signature 'treeSummarizedExperiment'
getByLink(x, subset)

`x`	A treeSummarizedExperiment object
`use.nodeLab`	A logical(1), indicating whether the rownames of assay elements should use node labels (the column `nodeLab` in `linkData` if there is not duplicated values; otherwise the column `nodeLab_alias` in `linkData` is used.)
`...`	For assay, ... contains `use.nodeLab`, which is forwarded to assays. For rowData, arguments passed through ... are forwarded to mcols.
`withDimnames`	A logical(1), indicating whether dimnames should be applied to extracted assay elements. Setting withDimnames=FALSE increases the speed and memory efficiency with which assays are extracted. withDimnames=TRUE in the getter assays<- allows efficient complex assignments (e.g., updating names of assays, names(assays(x, withDimnames=FALSE)) = ... is more efficient than names(assays(x)) = ...); it does not influence actual assignment of dimnames to assays.
`use.names`	Like `mcols(x)`, by default `rowData(x)` propagates the rownames of `x` to the returned DataFrame object (note that for a SummarizedExperiment object, the rownames are also the names i.e. `rownames(x)` is always the same as `names(x)`). Setting `use.names=FALSE` suppresses this propagation i.e. it returns a DataFrame object with no rownames. Use this when `rowData(x)` fails, which can happen when the rownames contain NAs (because the rownames of a SummarizedExperiment object can contain NAs, but the rownames of a DataFrame object cannot).
`i, j`	The subscripts that can act to subset the rows and columns of `x`, that is the matrix elements of assays.

Elements from treeSummarizedExperiment.

Ruizhu HUANG

treeSummarizedExperiment treeSummarizedExperiment-accessor leafSummarizedExperiment SummarizedExperiment-class

library(S4Vectors)
set.seed(1)
y <- matrix(rnbinom(300,size=1,mu=10),nrow=10)
colnames(y) <- paste(rep(LETTERS[1:3], each = 10), rep(1:10,3), sep = "_")
rownames(y) <- tinyTree$tip.label

rowInf <- DataFrame(nodeLab = rownames(y),
                    var1 = sample(letters[1:3], 10, replace = TRUE),
                    var2 = sample(c(TRUE, FALSE), 10, replace = TRUE))
colInf <- DataFrame(gg = factor(sample(1:3, 30, replace = TRUE)),
                    group = rep(LETTERS[1:3], each = 10))
toy_tse <- treeSummarizedExperiment(tree = tinyTree, rowData = rowInf,
                                    colData = colInf,
                                    assays = list(y, (2*y), 3*y))
rowData(toy_tse)
colData(toy_tse)
metadata(toy_tse)
linkData(toy_tse)
assays(toy_tse)