Description Usage Arguments Details Value Author(s) See Also Examples
TreeSummarizedExperiment constructs a TreeSummarizedExperiment object.
1 2 3 4 5 6 7 |
... |
Arguments passed to the |
rowTree |
A phylo object that provides hiearchical information of rows of assay tables. |
colTree |
A phylo object that provides hiearchical information of columns of assay tables. |
rowNodeLab |
A character string. It provides the labels of nodes that
the rows of |
colNodeLab |
A character string. It provides the labels of nodes that
the columns of |
The output TreeSummarizedExperiment object has very similar
structure as the
SingleCellExperiment. The
differences are summarized be as below.
rowTree A slot exists in TreeSummarizedExperiment
but not in SingleCellExperiment. It stores the tree structure(s)
that provide(s) hierarchical information of assays rows or columns
or both.
rowData If a phylo object is available in the slot
treeData to provide the hiearchical information about the rows of
the assays table, the rowData would be a
LinkDataFrame-class instead of
DataFrame. The data on the right side of the
vertical line provides the link information between the assays rows
and the tree phylo object, and could be accessed via
linkData; The data on the left side is the original rowData
like SingleCellExperiment object.
colData Similar to the explanaition for rowData as above.
More details about the LinkDataFrame in the rowData or
colData.
nodeLab The labels of nodes on the tree.
nodeLab\_alias The alias of node labels on the tree.
nodeNum The numbers of nodes on the tree.
isLeaf It indicates whether the node is a leaf node or internal node.
a TreeSummarizedExperiment object
Ruizhu HUANG
TreeSummarizedExperiment
TreeSummarizedExperiment-accessor
SingleCellExperiment
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | data("tinyTree")
# the count table
count <- matrix(rpois(100, 50), nrow = 10)
rownames(count) <- c(tinyTree$tip.label)
colnames(count) <- paste("C_", 1:10, sep = "_")
# The sample information
sampC <- data.frame(condition = rep(c("control", "trt"), each = 5),
gender = sample(x = 1:2, size = 10, replace = TRUE))
rownames(sampC) <- colnames(count)
# build a TreeSummarizedExperiment object
tse <- TreeSummarizedExperiment(assays = list(count),
colData = sampC,
rowTree = tinyTree)
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