aggTSE: Perform data aggregations based on the available tree...

In fionarhuang/TreeSummarizedExperiment: TreeSummarizedExperiment: a S4 Class for Data with Tree Structures

Description

aggTSE aggregates values on the leaf nodes of a tree to a specific arbitrary level of the tree. The level is specified via the nodes of the tree. Users could decide on which dimension (row or column) and how should the aggregation be performed.

Usage

aggTSE(
  x,
  rowLevel = NULL,
  rowBlock = NULL,
  colLevel = NULL,
  colBlock = NULL,
  rowFun = sum,
  colFun = sum,
  whichRowTree = 1,
  whichColTree = 1,
  whichAssay = NULL,
  message = FALSE,
  rowDataCols,
  colDataCols,
  rowFirst = TRUE,
  BPPARAM = NULL
)

Arguments

x	A TreeSummarizedExperiment object.
rowLevel	A numeric (node numbers) or character (node labels) vector. It provides the level on the tree that data is aggregated to. The aggregation is on the row dimension. The default is rowLevel = NULL, and no aggregation is performed.
rowBlock	A column name in the rowData to separate the aggregation.
colLevel	A numeric (node numbers) or character (node labels) vector. It provides the level on the tree that data is aggregated to. The aggregation is on the column dimension. The default is colLevel = NULL, and no aggregation is performed.
colBlock	A column name in the colData to separate the aggregation.
rowFun	A function to be applied on the row aggregation. It's similar to the FUN in apply.
colFun	A function to be applied on the col aggregation. It's similar to the FUN in apply.
whichRowTree	A integer scalar or string indicating which row tree is used in the aggregation. The first row tree is used as default.
whichColTree	A integer scalar or string indicating which row tree is used in the aggregation. The first row tree is used as default.
whichAssay	A integer scalar or string indicating which assay of x to use in the aggregation. If NULL, all assay tables are used in aggregation.
message	A logical value. The default is TRUE. If TRUE, it will print out the running process.
rowDataCols	The rowData columns to include.
colDataCols	The colData columns to include.
rowFirst	TRUE or FALSE. If the aggregation is in both dims., it is performed firstly on the row dim for rowFirst = TRUE or on the column dim for rowFirst = FALSE.
BPPARAM	Default is NULL and the computation isn't run in parallel. To run computation parallelly, an optional BiocParallelParam instance determining the parallel back-end to be used during evaluation, or a list of BiocParallelParam instances, to be applied in sequence for nested calls to BiocParallel functions.

Value

A TreeSummarizedExperiment object

Author(s)

Ruizhu HUANG

Examples

# assays data
set.seed(1)
toyTable <- matrix(rnbinom(20, size = 1, mu = 10), nrow = 5)
colnames(toyTable) <- paste(rep(LETTERS[1:2], each = 2),
                            rep(1:2, 2), sep = "_")
rownames(toyTable) <- paste("entity", seq_len(5), sep = "")

toyTable

# the column data
colInf <- DataFrame(gg = c(1, 2, 3, 3),
                    group = rep(LETTERS[1:2], each = 2),
                    row.names = colnames(toyTable))
colInf

# the toy tree
library(ape)
set.seed(4)
treeC <- rtree(4)
treeC$node.label <- c("All", "GroupA", "GroupB")

library(ggtree)
ggtree(treeC, size = 2) +
   geom_text2(aes(label = node), color = "darkblue",
           hjust = -0.5, vjust = 0.7, size = 6) +
    geom_text2(aes(label = label), color = "darkorange",
               hjust = -0.1, vjust = -0.7, size = 6)


tse <- TreeSummarizedExperiment(assays = list(toyTable),
                                colData = colInf,
                                colTree = treeC,
                                colNodeLab = treeC$tip.label,
                                metadata = list(test = 1:4))

aggCol <- aggTSE(x = tse, colLevel = c("GroupA", "GroupB"),
                 colFun = sum)

assays(aggCol)[[1]]

fionarhuang/TreeSummarizedExperiment documentation built on Aug. 18, 2021, 12:15 p.m.