,
Felix G.M. Ernst [ctb] | Title: | TreeSummarizedExperiment: a S4 Class for Data with Tree Structures |
|---|---|
| Description: | TreeSummarizedExperiment has extended SingleCellExperiment to include hierarchical information on the rows or columns of the rectangular data. |
| Authors: | Ruizhu Huang [aut, cre] ,
Felix G.M. Ernst [ctb] |
| Maintainer: | Ruizhu Huang <[email protected]> |
| License: | GPL (>=2) |
| Version: | 2.15.0 |
| Built: | 2024-11-26 06:10:02 UTC |
| Source: | https://github.com/bioc/TreeSummarizedExperiment |
TreeSummarizedExperiment packageTreeSummarizedExperiment implement a class of the same name, which
extends SingleCellExperiment to include hierarchical information on the rows
or columns of the rectangular data.
It also includes an additional slot for storing reference sequences per feature.
TreeSummarizedExperiment class
addLabel label nodes of a tree (phylo object)
addLabel(tree, label = NULL, on = c("all", "leaf", "internal"))addLabel(tree, label = NULL, on = c("all", "leaf", "internal"))
tree |
A phylo object |
label |
A character vector to provide node labels. The label is passed to
nodes that are sorted by their node number in ascending order. The default
is NULL, nodes are labeled by adding a prefix |
on |
Chosen from "all", "leaf", "internal". If "all", all nodes are labeled; if "leaf", leaves are labeled; if "internal", internal nodes are labeled. |
a phylo object
Ruizhu Huang
data(tinyTree) library(ggtree) # PLOT tree # The node labels are in orange texts and the node numbers are in blue ggtree(tinyTree, branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) # change labels nodes <- showNode(tree = tinyTree, only.leaf = FALSE) tt <- addLabel(tree = tinyTree, label = LETTERS[nodes], on = "all") ggtree(tt, branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7)data(tinyTree) library(ggtree) # PLOT tree # The node labels are in orange texts and the node numbers are in blue ggtree(tinyTree, branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) # change labels nodes <- showNode(tree = tinyTree, only.leaf = FALSE) tt <- addLabel(tree = tinyTree, label = LETTERS[nodes], on = "all") ggtree(tt, branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7)
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.
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 )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 )
x |
A |
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 |
rowBlock |
A column name in the |
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 |
colBlock |
A column name in the |
rowFun |
A function to be applied on the row aggregation. It's similar
to the |
colFun |
A function to be applied on the col aggregation. It's similar
to the |
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
|
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 |
BPPARAM |
Default is |
A TreeSummarizedExperiment object
Ruizhu HUANG
# 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]]# 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]]
aggValue 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.
aggValue( x, rowLevel = NULL, rowBlock = NULL, colLevel = NULL, colBlock = NULL, FUN = sum, assay = NULL, message = FALSE )aggValue( x, rowLevel = NULL, rowBlock = NULL, colLevel = NULL, colBlock = NULL, FUN = sum, assay = NULL, message = FALSE )
x |
A |
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 |
rowBlock |
A column name in the |
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 |
colBlock |
A column name in the |
FUN |
A function to be applied on the aggregation. It's similar to the
|
assay |
A integer scalar or string indicating which assay of |
message |
A logical value. The default is TRUE. If TRUE, it will print out the running process. |
A TreeSummarizedExperiment object or a
matrix. The output has the same class of the input x.
Ruizhu HUANG
asLeaf updates a phylo tree by changing the specified internal
nodes to leaf nodes. In other words, the descendant nodes of the specified
internal nodes are removed.
asLeaf(tree, node)asLeaf(tree, node)
tree |
A phylo object. |
node |
A numeric or character vector. It specifies internal nodes that are changed to leaves via their node labels or numbers. |
A phylo object.
library(ggtree) data(tinyTree) ggtree(tinyTree, ladderize = FALSE) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) + geom_hilight(node = 16) + geom_point2() # remove the blue branch NT1 <- asLeaf(tree = tinyTree, node = 16) ggtree(NT1, ladderize = FALSE) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_point2() # if mergeSingle = TRUE, the node (Node_17) is removed. NT2 <- asLeaf(tree = tinyTree, node = c(15, 13)) ggtree(NT2, ladderize = FALSE) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_point2()library(ggtree) data(tinyTree) ggtree(tinyTree, ladderize = FALSE) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) + geom_hilight(node = 16) + geom_point2() # remove the blue branch NT1 <- asLeaf(tree = tinyTree, node = 16) ggtree(NT1, ladderize = FALSE) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_point2() # if mergeSingle = TRUE, the node (Node_17) is removed. NT2 <- asLeaf(tree = tinyTree, node = c(15, 13)) ggtree(NT2, ladderize = FALSE) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_point2()
asPhylo converts a data frame to a phylo object. Compared to
toTree, asPhylo allows the output tree to have different number
of nodes in paths connecting leaves to the root.
asPhylo(data, column_order = NULL, asNA = NULL)asPhylo(data, column_order = NULL, asNA = NULL)
data |
A data frame or matrix. |
column_order |
A vector that includes the column names of data to
reorder columns of |
asNA |
This specifies strings that are considered as NA |
The last column is used as the leaf nodes
a phylo object
Ruizhu Huang
library(ggtree) # Example 0: taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 4)), R3 = paste0("C", 1:5)) # Internal nodes: their labels are prefixed with colnames of taxTab # e.g., R2:B2 taxTree <- asPhylo(data = taxTab) ggtree(taxTree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint() # (Below gives the same output as toTree) taxTab$R1 <- paste0("R1:", taxTab$R1) taxTab$R2 <- paste0("R2:", taxTab$R2) taxTree <- asPhylo(data = taxTab) # viz the tree ggtree(taxTree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint() # Example 1 df1 <- rbind.data.frame(c("root", "A1", "A2", NA), c("root", "B1", NA, NA)) colnames(df1) <- paste0("L", 1:4) tree1 <- asPhylo(df1) ggtree(tree1, color = "grey") + geom_nodepoint() + geom_text2(aes(label = label), angle = 90, color = "red", vjust = 2, size = 4) # Example 2 df2 <- data.frame(Group_1 = rep("Root", 11), Group_2 = rep(c(13, 21), c(9, 2)), Group_3 = rep(c(14, 18, "unknown"), c(5, 4, 2)), Group_4 = rep(c(15, "unknown", 19, "unknown"), c(4, 1, 3, 3)), Group_5 = rep(c(16, "unknown", 20, "unknown"), c(3, 2, 2, 4)), Group_6 = rep(c(17, "unknown"), c(2, 9)), LEAF = 1:11) tree2 <- asPhylo(df2, asNA = "unknown") ggtree(tree2, color = "grey") + geom_nodepoint() + geom_text2(aes(label = label), angle = 90, color = "red", vjust = 2, size = 4) # Example 3 df3 <- df2 df3[10:11, 3] <- "" tree3 <- asPhylo(df3, asNA = c("unknown", "")) ggtree(tree3, color = "grey") + geom_nodepoint() + geom_text2(aes(label = label), angle = 90, color = "red", vjust = 2, size = 4)library(ggtree) # Example 0: taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 4)), R3 = paste0("C", 1:5)) # Internal nodes: their labels are prefixed with colnames of taxTab # e.g., R2:B2 taxTree <- asPhylo(data = taxTab) ggtree(taxTree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint() # (Below gives the same output as toTree) taxTab$R1 <- paste0("R1:", taxTab$R1) taxTab$R2 <- paste0("R2:", taxTab$R2) taxTree <- asPhylo(data = taxTab) # viz the tree ggtree(taxTree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint() # Example 1 df1 <- rbind.data.frame(c("root", "A1", "A2", NA), c("root", "B1", NA, NA)) colnames(df1) <- paste0("L", 1:4) tree1 <- asPhylo(df1) ggtree(tree1, color = "grey") + geom_nodepoint() + geom_text2(aes(label = label), angle = 90, color = "red", vjust = 2, size = 4) # Example 2 df2 <- data.frame(Group_1 = rep("Root", 11), Group_2 = rep(c(13, 21), c(9, 2)), Group_3 = rep(c(14, 18, "unknown"), c(5, 4, 2)), Group_4 = rep(c(15, "unknown", 19, "unknown"), c(4, 1, 3, 3)), Group_5 = rep(c(16, "unknown", 20, "unknown"), c(3, 2, 2, 4)), Group_6 = rep(c(17, "unknown"), c(2, 9)), LEAF = 1:11) tree2 <- asPhylo(df2, asNA = "unknown") ggtree(tree2, color = "grey") + geom_nodepoint() + geom_text2(aes(label = label), angle = 90, color = "red", vjust = 2, size = 4) # Example 3 df3 <- df2 df3[10:11, 3] <- "" tree3 <- asPhylo(df3, asNA = c("unknown", "")) ggtree(tree3, color = "grey") + geom_nodepoint() + geom_text2(aes(label = label), angle = 90, color = "red", vjust = 2, size = 4)
changeTree changes a row or column tree in a
TreeSummarizedExperiment object.
changeTree( x, rowTree = NULL, rowNodeLab = NULL, colTree = NULL, colNodeLab = NULL, whichRowTree = 1, whichColTree = 1 )changeTree( x, rowTree = NULL, rowNodeLab = NULL, colTree = NULL, colNodeLab = NULL, whichRowTree = 1, whichColTree = 1 )
x |
A TreeSummarizedExperiment object |
rowTree |
A phylo object. A new row tree. |
rowNodeLab |
A character string. It provides the labels of nodes that the rows of assays tables corresponding to. If NULL (default), the row names of the assays tables are used. |
colTree |
A phylo object. A new column tree. |
colNodeLab |
A character string. It provides the labels of nodes that the columns of assays tables corresponding to. If NULL (default), the column names of the assays tables are used. |
whichRowTree |
Which row tree to be replaced? Default is 1 (the first
tree in the |
whichColTree |
Which column tree to be replaced? Default is 1 (the first
tree in the |
A TreeSummarizedExperiment object
Ruizhu Huang
library(ape) set.seed(1) treeR <- ape::rtree(10) # the count table count <- matrix(rpois(160, 50), nrow = 20) rownames(count) <- paste0("entity", 1:20) colnames(count) <- paste("sample", 1:8, sep = "_") # The sample information sampC <- data.frame(condition = rep(c("control", "trt"), each = 4), gender = sample(x = 1:2, size = 8, replace = TRUE)) rownames(sampC) <- colnames(count) # build a TreeSummarizedExperiment object tse <- TreeSummarizedExperiment(assays = list(count), colData = sampC, rowTree = treeR, rowNodeLab = rep(treeR$tip.label, each =2)) treeR2 <- drop.tip(phy = treeR, tip = c("t10", "t9", "t8")) # if rownames are not used in node labels of the tree, provide rowNodeLab use <- changeTree(x = tse, rowTree = treeR2, rowNodeLab = rep(treeR$tip.label, each =2)) use # if rownames are used in node labels of tree, rowNodeLab is not required. rownames(tse) <- rep(treeR$tip.label, each =2) cse <- changeTree(x = tse, rowTree = treeR2) cselibrary(ape) set.seed(1) treeR <- ape::rtree(10) # the count table count <- matrix(rpois(160, 50), nrow = 20) rownames(count) <- paste0("entity", 1:20) colnames(count) <- paste("sample", 1:8, sep = "_") # The sample information sampC <- data.frame(condition = rep(c("control", "trt"), each = 4), gender = sample(x = 1:2, size = 8, replace = TRUE)) rownames(sampC) <- colnames(count) # build a TreeSummarizedExperiment object tse <- TreeSummarizedExperiment(assays = list(count), colData = sampC, rowTree = treeR, rowNodeLab = rep(treeR$tip.label, each =2)) treeR2 <- drop.tip(phy = treeR, tip = c("t10", "t9", "t8")) # if rownames are not used in node labels of the tree, provide rowNodeLab use <- changeTree(x = tse, rowTree = treeR2, rowNodeLab = rep(treeR$tip.label, each =2)) use # if rownames are used in node labels of tree, rowNodeLab is not required. rownames(tse) <- rep(treeR$tip.label, each =2) cse <- changeTree(x = tse, rowTree = treeR2) cse
countLeaf calculates the number of leaves on a phylo tree.
countLeaf(tree)countLeaf(tree)
tree |
A phylo object |
a numeric value
Ruizhu Huang
library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue') (n <- countLeaf(tinyTree))library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue') (n <- countLeaf(tinyTree))
countNode calculates the number of nodes on a phylo tree.
countNode(tree)countNode(tree)
tree |
A phylo object |
a numeric value
Ruizhu Huang
library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue') (n <- countNode(tinyTree))library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue') (n <- countNode(tinyTree))
detectLoop detects loopsDetect loops
detectLoop detects loops
detectLoop(tax_tab)detectLoop(tax_tab)
tax_tab |
a data frame where columns store hierarchical levels. The columns from the left to the right correspond nodes from the root to the leaf. |
a data frame
Ruizhu Huang
df <- data.frame(A = rep("a", 8), B = rep (c("b1", "b2", "b3", "b4"), each = 2), C = paste0("c", c(1, 2, 2, 3:7)), D = paste0("d", 1:8)) # The result means that a loop is caused by 'b1' and 'b2' in column 'B' and # 'c2' in column 'C' (a-b1-c2; a-b2-c2) detectLoop(tax_tab = df) df <- data.frame(R1 = rep("A", 6), R2 = c("B1", rep("B2", 4), "B3"), R3 = c("C1", "C2", "C3", NA, NA, NA), R4 = c("D1", "D2", "D3", NA, NA, NA), R5 = paste0("E", 1:6)) detectLoop(tax_tab = df) df <- data.frame(R1 = rep("A", 7), R2 = c("B1", rep("B2", 4), "B3", "B3"), R3 = c("C1", "C2", "C3", "", "", "", ""), R4 = c("D1", "D2", "D3", "", "", "", ""), R5 = paste0("E", 1:7)) detectLoop(tax_tab = df) df <- data.frame(R1 = rep("A", 7), R2 = c("B1", rep("B2", 4), "B3", "B3"), R3 = c("C1", "C2", "C3", NA, NA, NA, NA), R4 = c("D1", "D2", "D3", NA, NA, NA, NA), R5 = paste0("E", 1:7)) detectLoop(tax_tab = df)df <- data.frame(A = rep("a", 8), B = rep (c("b1", "b2", "b3", "b4"), each = 2), C = paste0("c", c(1, 2, 2, 3:7)), D = paste0("d", 1:8)) # The result means that a loop is caused by 'b1' and 'b2' in column 'B' and # 'c2' in column 'C' (a-b1-c2; a-b2-c2) detectLoop(tax_tab = df) df <- data.frame(R1 = rep("A", 6), R2 = c("B1", rep("B2", 4), "B3"), R3 = c("C1", "C2", "C3", NA, NA, NA), R4 = c("D1", "D2", "D3", NA, NA, NA), R5 = paste0("E", 1:6)) detectLoop(tax_tab = df) df <- data.frame(R1 = rep("A", 7), R2 = c("B1", rep("B2", 4), "B3", "B3"), R3 = c("C1", "C2", "C3", "", "", "", ""), R4 = c("D1", "D2", "D3", "", "", "", ""), R5 = paste0("E", 1:7)) detectLoop(tax_tab = df) df <- data.frame(R1 = rep("A", 7), R2 = c("B1", rep("B2", 4), "B3", "B3"), R3 = c("C1", "C2", "C3", NA, NA, NA, NA), R4 = c("D1", "D2", "D3", NA, NA, NA, NA), R5 = paste0("E", 1:7)) detectLoop(tax_tab = df)
distNode is to calculate the distance between any two nodes on
a phylo tree
distNode(tree, node)distNode(tree, node)
tree |
A phylo object. |
node |
A numeric or character vector of length two. |
A numeric value.
library(ggtree) data(tinyTree) ggtree(tinyTree) + geom_text2(aes(label = node), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = branch.length), color = "darkblue", vjust = 0.7) distNode(tree = tinyTree, node = c(10, 11)) distNode(tree = tinyTree, node = c(12, 13)) distNode(tree = tinyTree, node = c(13, 15)) distNode(tree = tinyTree, node = c(12, 14))library(ggtree) data(tinyTree) ggtree(tinyTree) + geom_text2(aes(label = node), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = branch.length), color = "darkblue", vjust = 0.7) distNode(tree = tinyTree, node = c(10, 11)) distNode(tree = tinyTree, node = c(12, 13)) distNode(tree = tinyTree, node = c(13, 15)) distNode(tree = tinyTree, node = c(12, 14))
findAncestor finds the ancestor in the nth generation above
specified nodes.
findAncestor(tree, node, level, use.alias = FALSE)findAncestor(tree, node, level, use.alias = FALSE)
tree |
A phylo object |
node |
A vector of node numbers or node labels |
level |
A vector of numbers to define nth generation before the specified nodes |
use.alias |
A logical value, TRUE or FALSE. The default is FALSE, and
the node label would be used to name the output; otherwise, the alias of
node label would be used to name the output. The alias of node label is
created by adding a prefix |
A vector of nodes. The numeric value is the node number, and the
vector name is the corresponding node label. If a node has no label, it
would have NA as name when use.alias = FALSE, and have the alias of
node label as name when use.alias = TRUE.
Ruizhu Huang
library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) findAncestor(tree = tinyTree, node = c(18, 13), level = 1)library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) findAncestor(tree = tinyTree, node = c(18, 13), level = 1)
findChild finds children of an internal node.
findChild(tree, node = 11, use.alias = FALSE)findChild(tree, node = 11, use.alias = FALSE)
tree |
A phylo object. |
node |
An internal node. It could be the node number or the node label. |
use.alias |
A logical value, TRUE or FALSE. The default is FALSE, and
the node label would be used to name the output; otherwise, the alias of
node label would be used to name the output. The alias of node label is
created by adding a prefix |
A vector of nodes. The numeric value is the node number, and the
vector name is the corresponding node label. If a node has no label, it
would have NA as name when use.alias = FALSE, and have the alias of
node label as name when use.alias = TRUE.
Ruizhu Huang
data(tinyTree) library(ggtree) ggtree(tinyTree) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) + geom_hilight(node = 17, fill = 'steelblue', alpha = 0.5) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) (tips <- findChild(tree = tinyTree, node = 17))data(tinyTree) library(ggtree) ggtree(tinyTree) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) + geom_hilight(node = 17, fill = 'steelblue', alpha = 0.5) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) (tips <- findChild(tree = tinyTree, node = 17))
findDescendant finds descendants of a node.
findOS(tree, node, only.leaf = TRUE, self.include = FALSE, use.alias = FALSE) findDescendant( tree, node, only.leaf = TRUE, self.include = FALSE, use.alias = FALSE )findOS(tree, node, only.leaf = TRUE, self.include = FALSE, use.alias = FALSE) findDescendant( tree, node, only.leaf = TRUE, self.include = FALSE, use.alias = FALSE )
tree |
A phylo object. |
node |
An internal node. It could be the node number or the node label. |
only.leaf |
A logical value, TRUE or FALSE. The default is TRUE. If default, only the leaf nodes in the descendant nodes would be returned. |
self.include |
A logical value, TRUE or FALSE. The default is FALSE. If TRUE, the node specified in node is included and the leaf node itself is returned as its descendant. |
use.alias |
A logical value, TRUE or FALSE. The default is FALSE, and
the node label would be used to name the output; otherwise, the alias of
node label would be used to name the output. The alias of node label is
created by adding a prefix |
A vector of nodes. The numeric value is the node number, and the
vector name is the corresponding node label. If a node has no label, it
would have NA as name when use.alias = FALSE, and have the alias of
node label as name when use.alias = TRUE.
Ruizhu Huang
data(tinyTree) library(ggtree) ggtree(tinyTree) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) + geom_hilight(node = 17, fill = 'steelblue', alpha = 0.5) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) (tips <- findDescendant(tree = tinyTree, node = c(17), only.leaf = TRUE))data(tinyTree) library(ggtree) ggtree(tinyTree) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) + geom_hilight(node = 17, fill = 'steelblue', alpha = 0.5) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) (tips <- findDescendant(tree = tinyTree, node = c(17), only.leaf = TRUE))
findSibling is to find the sibling node of an node node.
findSibling(tree, node, use.alias = FALSE)findSibling(tree, node, use.alias = FALSE)
tree |
A phylo object. |
node |
A numeric or character vector. Node labels or node numbers. |
use.alias |
A logical value, TRUE or FALSE. The default is FALSE, and
the original node label would be used to name the output; otherwise, the
alias of node label would be used to name the output. The alias of node
label is created by adding a prefix |
A vector of nodes. The numeric value is the node number, and the
vector name is the corresponding node label. If a node has no label, it
would have NA as name when use.alias = FALSE, and have the alias of
node label as name when use.alias = TRUE.
library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) findSibling(tree = tinyTree, node = 17) findSibling(tree = tinyTree, node = c(13, 17))library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) findSibling(tree = tinyTree, node = 17) findSibling(tree = tinyTree, node = c(13, 17))
isLeaf is to test wheter some specified nodes are leaf nodes of a
tree.
isLeaf(tree, node)isLeaf(tree, node)
tree |
A phylo object. |
node |
A numeric or character vector. Node labels or node numbers. |
a logical vector with the same length as the input node.
Ruizhu HUANG
data(tinyTree) library(ggtree) # PLOT tree # The node labels are in orange texts and the node numbers are in blue ggtree(tinyTree,branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) isLeaf(tree = tinyTree, node = c(5, 4, 18)) isLeaf(tree = tinyTree, node = c("t4", "t9", "Node_18" ))data(tinyTree) library(ggtree) # PLOT tree # The node labels are in orange texts and the node numbers are in blue ggtree(tinyTree,branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) isLeaf(tree = tinyTree, node = c(5, 4, 18)) isLeaf(tree = tinyTree, node = c("t4", "t9", "Node_18" ))
The LinkDataFrame is extended from the class DataFrame to
include at least four columns nodeLab, nodeLab_alias,
nodeNum, and isLeaf.
See LinkDataFrame-constructor for constructor
functions.
Construct a LinkDataFrame Construct a LinkDataFrame object
LinkDataFrame(nodeLab, nodeLab_alias, nodeNum, isLeaf, whichTree, ...)LinkDataFrame(nodeLab, nodeLab_alias, nodeNum, isLeaf, whichTree, ...)
nodeLab |
A character vector |
nodeLab_alias |
A character vector |
nodeNum |
A numeric vector |
isLeaf |
A logical vector |
whichTree |
A character vector |
... |
All arguments accepted by
|
A LinkDataFrame object
(ld <- LinkDataFrame(nodeLab = letters[1:5], nodeLab_alias = LETTERS[1:5], nodeNum = 1:5, isLeaf = TRUE, whichTree = LETTERS[1:5], right = 1:5))(ld <- LinkDataFrame(nodeLab = letters[1:5], nodeLab_alias = LETTERS[1:5], nodeNum = 1:5, isLeaf = TRUE, whichTree = LETTERS[1:5], right = 1:5))
makeTSE creates a toy TreeSummarizedExperiment object.
makeTSE(nrow = 10, ncol = 4, include.rowTree = TRUE, include.colTree = TRUE)makeTSE(nrow = 10, ncol = 4, include.rowTree = TRUE, include.colTree = TRUE)
nrow |
a numeric value to specify the number of rows of
|
ncol |
a numeric value to specify the number of columns of
|
include.rowTree |
TRUE or FALSE. Default is TRUE, so the output
|
include.colTree |
TRUE or FALSE. Default is TRUE, so the output
|
The assays contains a matrix with values from
1:(nrow*ncol). The rowData has two columns, var1 and
var2. var1 is created with rep_len(letters, nrow).
var2 is created with rep_len(c(TRUE, FALSE), nrow). The
colData has two columns, ID and group. ID is
created with seq_len(ncol). group is created with
rep_len(LETTERS[1:2], ncol). The row/col tree is generated with
ape::rtree(). So, to generate reproducible trees, set.seed()
is required.
A TreeSummarizedExperiment object
Ruizhu Huang
set.seed(1) makeTSE()set.seed(1) makeTSE()
matTree transforms a phylo tree into a matrix. The entry of the matrix
is node number. Each row represents a path connecting a leaf node and the
root. The columns are arranged in the order as the path passing the nodes to
reach the root.
matTree(tree)matTree(tree)
tree |
A phylo object |
A matrix
Ruizhu Huang
library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = node)) # each row of the matrix representing a path. # the first column is leaf nodes; the last non-NA value in a row is the root mat <- matTree(tree = tinyTree)library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = node)) # each row of the matrix representing a path. # the first column is leaf nodes; the last non-NA value in a row is the root mat <- matTree(tree = tinyTree)
nodeLabel is to print out the node labels of a phylo tree.
printNode(tree, type = c("leaf", "internal", "all"))printNode(tree, type = c("leaf", "internal", "all"))
tree |
A phylo object. |
type |
A character value choose from |
a data frame
Ruizhu HUANG
data(tinyTree) library(ggtree) # PLOT tree # The node labels are in orange texts and the node numbers are in blue ggtree(tinyTree,branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) (pn1 <- printNode(tinyTree, type = "leaf")) (pn2 <- printNode(tinyTree, type = "internal")) (pn3 <- printNode(tinyTree, type = "all"))data(tinyTree) library(ggtree) # PLOT tree # The node labels are in orange texts and the node numbers are in blue ggtree(tinyTree,branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) (pn1 <- printNode(tinyTree, type = "leaf")) (pn2 <- printNode(tinyTree, type = "internal")) (pn3 <- printNode(tinyTree, type = "all"))
rbind and cbind take one or more
TreeSummarizedExperiment objects and combine them by columns or rows,
respectively.
## S4 method for signature 'TreeSummarizedExperiment' rbind(..., deparse.level = 1) ## S4 method for signature 'TreeSummarizedExperiment' cbind(..., deparse.level = 1)## S4 method for signature 'TreeSummarizedExperiment' rbind(..., deparse.level = 1) ## S4 method for signature 'TreeSummarizedExperiment' cbind(..., deparse.level = 1)
... |
One or more |
deparse.level |
See |
A TreeSummarizedExperiment object
Ruizhu Huang
# rbind works : # a) TSE without rowTree and without colTree # b) TSE with rowTree but without colTree # c) TSE without rowTree but with colTree # d) TSE with rowTree & colTree set.seed(1) # a) (tse_a <- makeTSE(include.colTree = FALSE)) (tse_b <- makeTSE(include.colTree = FALSE)) # b) (tse_c <- makeTSE(include.rowTree = FALSE)) (tse_d <- makeTSE(include.rowTree = FALSE)) rbind(tse_a, tse_b) cbind(tse_c, tse_d)# rbind works : # a) TSE without rowTree and without colTree # b) TSE with rowTree but without colTree # c) TSE without rowTree but with colTree # d) TSE with rowTree & colTree set.seed(1) # a) (tse_a <- makeTSE(include.colTree = FALSE)) (tse_b <- makeTSE(include.colTree = FALSE)) # b) (tse_c <- makeTSE(include.rowTree = FALSE)) (tse_d <- makeTSE(include.rowTree = FALSE)) rbind(tse_a, tse_b) cbind(tse_c, tse_d)
resolveLoop resolve loops by adding suffix to the child node. The
suffix is "_i" where 'i' is a number. Please see examples.Resolve loops
resolveLoop resolve loops by adding suffix to the child node. The
suffix is "_i" where 'i' is a number. Please see examples.
resolveLoop(tax_tab)resolveLoop(tax_tab)
tax_tab |
a data frame where columns store hierarchical levels. The columns from the left to the right correspond nodes from the root to the leaf. |
a data frame
Ruizhu Huang
# example 1 df <- data.frame(A = rep("a", 8), B = rep (c("b1", "b2", "b3", "b4"), each = 2), C = paste0("c", c(1, 2, 2, 3:7)), D = paste0("d", 1:8)) # The result means that a loop is caused by 'b1' and 'b2' in column 'B' and # 'c2' in column 'C' (a-b1-c2; a-b2-c2) resolveLoop(tax_tab = df) # example 2 taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 3), ""), R3 = c("C1", "C2", "C3", "", ""), R4 = c("D1", "D2", "D3", "", ""), R5 = paste0("E", 1:5)) resolveLoop(tax_tab = taxTab) # example 3 taxTab <- data.frame(R1 = rep("A", 6), R2 = c("B1", rep("B2", 4), ""), R3 = c("C1", "C2", "C3", "", "", ""), R4 = c("D1", "D2", "D3", "", "", ""), R5 = paste0("E", 1:6)) resolveLoop(tax_tab = taxTab) # example 3 taxTab <- data.frame( R1 = rep("A", 5), R2 = c("B1", rep("B2", 3), "B3"), R3 = c("C1", "C2", "C3", NA, NA), R4 = c("D1", "D2", "D3", NA, NA), R5 = paste0("E", 1:5)) resolveLoop(tax_tab = taxTab)# example 1 df <- data.frame(A = rep("a", 8), B = rep (c("b1", "b2", "b3", "b4"), each = 2), C = paste0("c", c(1, 2, 2, 3:7)), D = paste0("d", 1:8)) # The result means that a loop is caused by 'b1' and 'b2' in column 'B' and # 'c2' in column 'C' (a-b1-c2; a-b2-c2) resolveLoop(tax_tab = df) # example 2 taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 3), ""), R3 = c("C1", "C2", "C3", "", ""), R4 = c("D1", "D2", "D3", "", ""), R5 = paste0("E", 1:5)) resolveLoop(tax_tab = taxTab) # example 3 taxTab <- data.frame(R1 = rep("A", 6), R2 = c("B1", rep("B2", 4), ""), R3 = c("C1", "C2", "C3", "", "", ""), R4 = c("D1", "D2", "D3", "", "", ""), R5 = paste0("E", 1:6)) resolveLoop(tax_tab = taxTab) # example 3 taxTab <- data.frame( R1 = rep("A", 5), R2 = c("B1", rep("B2", 3), "B3"), R3 = c("C1", "C2", "C3", NA, NA), R4 = c("D1", "D2", "D3", NA, NA), R5 = paste0("E", 1:5)) resolveLoop(tax_tab = taxTab)
All accessor functions that work on
SingleCellExperiment
should work on TreeSummarizedExperiment. Additionally, new accessors
rowLinks colLinks, rowTree and colTree accessor
function are available for TreeSummarizedExperiment.
rowLinks(x) ## S4 method for signature 'TreeSummarizedExperiment' rowLinks(x) colLinks(x) ## S4 method for signature 'TreeSummarizedExperiment' colLinks(x) rowTree(x, whichTree = 1, value) ## S4 method for signature 'TreeSummarizedExperiment' rowTree(x, whichTree = 1, value) rowTree(x, whichTree = 1) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' rowTree(x, whichTree = 1) <- value colTree(x, whichTree = 1) ## S4 method for signature 'TreeSummarizedExperiment' colTree(x, whichTree = 1) colTree(x, whichTree = 1) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' colTree(x, whichTree = 1) <- value rowTreeNames(x, value) ## S4 method for signature 'TreeSummarizedExperiment' rowTreeNames(x, value) rowTreeNames(x) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' rowTreeNames(x) <- value colTreeNames(x, value) ## S4 method for signature 'TreeSummarizedExperiment' colTreeNames(x, value) colTreeNames(x) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' colTreeNames(x) <- value referenceSeq(x) ## S4 method for signature 'TreeSummarizedExperiment' referenceSeq(x) referenceSeq(x) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' referenceSeq(x) <- value ## S4 method for signature 'TreeSummarizedExperiment,ANY,ANY,ANY' x[i, j, ..., drop = TRUE] ## S4 replacement method for signature ## 'TreeSummarizedExperiment,ANY,ANY,TreeSummarizedExperiment' x[i, j, ...] <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' rownames(x) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' colnames(x) <- value subsetByLeaf( x, rowLeaf, colLeaf, whichRowTree, whichColTree, updateTree = TRUE ) ## S4 method for signature 'TreeSummarizedExperiment' subsetByLeaf( x, rowLeaf, colLeaf, whichRowTree, whichColTree, updateTree = TRUE ) subsetByNode(x, rowNode, colNode, whichRowTree, whichColTree) ## S4 method for signature 'TreeSummarizedExperiment' subsetByNode(x, rowNode, colNode, whichRowTree, whichColTree)rowLinks(x) ## S4 method for signature 'TreeSummarizedExperiment' rowLinks(x) colLinks(x) ## S4 method for signature 'TreeSummarizedExperiment' colLinks(x) rowTree(x, whichTree = 1, value) ## S4 method for signature 'TreeSummarizedExperiment' rowTree(x, whichTree = 1, value) rowTree(x, whichTree = 1) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' rowTree(x, whichTree = 1) <- value colTree(x, whichTree = 1) ## S4 method for signature 'TreeSummarizedExperiment' colTree(x, whichTree = 1) colTree(x, whichTree = 1) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' colTree(x, whichTree = 1) <- value rowTreeNames(x, value) ## S4 method for signature 'TreeSummarizedExperiment' rowTreeNames(x, value) rowTreeNames(x) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' rowTreeNames(x) <- value colTreeNames(x, value) ## S4 method for signature 'TreeSummarizedExperiment' colTreeNames(x, value) colTreeNames(x) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' colTreeNames(x) <- value referenceSeq(x) ## S4 method for signature 'TreeSummarizedExperiment' referenceSeq(x) referenceSeq(x) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' referenceSeq(x) <- value ## S4 method for signature 'TreeSummarizedExperiment,ANY,ANY,ANY' x[i, j, ..., drop = TRUE] ## S4 replacement method for signature ## 'TreeSummarizedExperiment,ANY,ANY,TreeSummarizedExperiment' x[i, j, ...] <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' rownames(x) <- value ## S4 replacement method for signature 'TreeSummarizedExperiment' colnames(x) <- value subsetByLeaf( x, rowLeaf, colLeaf, whichRowTree, whichColTree, updateTree = TRUE ) ## S4 method for signature 'TreeSummarizedExperiment' subsetByLeaf( x, rowLeaf, colLeaf, whichRowTree, whichColTree, updateTree = TRUE ) subsetByNode(x, rowNode, colNode, whichRowTree, whichColTree) ## S4 method for signature 'TreeSummarizedExperiment' subsetByNode(x, rowNode, colNode, whichRowTree, whichColTree)
x |
A TreeSummarizedExperiment object |
whichTree |
A numeric indicator or name character to specify which tree
in the |
value |
|
i, j
|
The row, column index to subset |
... |
The argument from the subset function |
drop |
A logical value, TRUE or FALSE. The argument from the subset
function |
rowLeaf |
A vector of leaves that are used to subset rows. One could use the leaf number, or the leaf label to specify nodes, but not a mixture of them. |
colLeaf |
A vector of leaves that are used to subset columns. One could use the leaf number, or the leaf label to specify nodes, but not a mixture of them. |
whichRowTree |
A numeric indicator or name character to specify which tree
in the |
whichColTree |
A numeric indicator or name character to specify which tree
in the |
updateTree |
TRUE or FALSE. Default is TRUE, which updates tree structures after subsetting. |
rowNode |
A vector of nodes that are used to subset rows. One could use the node number, the node label or the node alias to specify nodes, but not a mixture of them. |
colNode |
A vector of nodes that are used to subset columns. One could use the node number, the node label or the node alias to specify nodes, but not a mixture of them. |
Elements from TreeSummarizedExperiment.
Ruizhu HUANG
TreeSummarizedExperiment
SingleCellExperiment
# the assay table 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$tip.label # the row data rowInf <- DataFrame(var1 = sample(letters[1:3], 10, replace = TRUE), var2 = sample(c(TRUE, FALSE), 10, replace = TRUE)) # the column data colInf <- DataFrame(gg = factor(sample(1:3, 30, replace = TRUE)), group = rep(LETTERS[1:3], each = 10)) # the tree structure on the rows of assay tables data("tinyTree") # the tree structure on the columns of assay tables sampTree <- ape::rtree(30) sampTree$tip.label <- colnames(y) # create the TreeSummarizedExperiment object toy_tse <- TreeSummarizedExperiment(assays = list(y), rowData = rowInf, colData = colInf, rowTree = tinyTree, colTree = sampTree) ## extract the rowData (rowD <- rowData(x = toy_tse)) ## extract the colData (colD <- colData(x = toy_tse)) ## extract the linkData # on rows (rowL <- rowLinks(x = toy_tse)) # on columns (colL <- colLinks(x = toy_tse)) ## extract the treeData # on rows (rowT <- rowTree(x = toy_tse)) # on columns (colT <- colTree(x = toy_tse)) # the referenceSeq data refSeq <- DNAStringSetList(one = DNAStringSet(rep("A",nrow(toy_tse))), two = DNAStringSet(rep("B",nrow(toy_tse)))) referenceSeq(toy_tse) <- refSeq toy_tse # subset treeSE by leaves library(ape) set.seed(1) z <- makeTSE(nrow = 5, ncol = 4, include.rowTree = TRUE, include.colTree = FALSE) y <- makeTSE(nrow = 4, ncol = 4, include.rowTree = TRUE, include.colTree = FALSE) tr <- ape::rtree(4) zy <- rbind(z, y) x <- changeTree(x = zy, rowTree = tr, whichRowTree = 2, rowNodeLab = tr$tip.label) rowLinks(zy) rowLinks(x) ## 1) rowLeaf exist only in one of trees rf <- c("t1", "t3") sx <- subsetByLeaf(x = x, rowLeaf = rf) rowLinks(sx) sx <- subsetByLeaf(x = x, rowLeaf = rf, updateTree = FALSE) rowLinks(sx) ## 2) rowLeaf exist in all trees rf <- 1:3 sxx <- subsetByLeaf(x = x, rowLeaf = rf) rowLinks(sxx) ## 3) rowLeaf exist in all trees, but subset and update only the specified trees rf <- c(3:4) sxx <- subsetByLeaf(x = x, rowLeaf = rf, whichRowTree = "phylo") rowLinks(sxx)# the assay table set.seed(1) y <- matrix(rnbinom(300,size=1,mu=10),nrow=10) colnames(y) <- paste(rep(LETTERS[1:3], each = 10), rep(1:10,3), sep = "_") rownames(y) <- tinyTree$tip.label # the row data rowInf <- DataFrame(var1 = sample(letters[1:3], 10, replace = TRUE), var2 = sample(c(TRUE, FALSE), 10, replace = TRUE)) # the column data colInf <- DataFrame(gg = factor(sample(1:3, 30, replace = TRUE)), group = rep(LETTERS[1:3], each = 10)) # the tree structure on the rows of assay tables data("tinyTree") # the tree structure on the columns of assay tables sampTree <- ape::rtree(30) sampTree$tip.label <- colnames(y) # create the TreeSummarizedExperiment object toy_tse <- TreeSummarizedExperiment(assays = list(y), rowData = rowInf, colData = colInf, rowTree = tinyTree, colTree = sampTree) ## extract the rowData (rowD <- rowData(x = toy_tse)) ## extract the colData (colD <- colData(x = toy_tse)) ## extract the linkData # on rows (rowL <- rowLinks(x = toy_tse)) # on columns (colL <- colLinks(x = toy_tse)) ## extract the treeData # on rows (rowT <- rowTree(x = toy_tse)) # on columns (colT <- colTree(x = toy_tse)) # the referenceSeq data refSeq <- DNAStringSetList(one = DNAStringSet(rep("A",nrow(toy_tse))), two = DNAStringSet(rep("B",nrow(toy_tse)))) referenceSeq(toy_tse) <- refSeq toy_tse # subset treeSE by leaves library(ape) set.seed(1) z <- makeTSE(nrow = 5, ncol = 4, include.rowTree = TRUE, include.colTree = FALSE) y <- makeTSE(nrow = 4, ncol = 4, include.rowTree = TRUE, include.colTree = FALSE) tr <- ape::rtree(4) zy <- rbind(z, y) x <- changeTree(x = zy, rowTree = tr, whichRowTree = 2, rowNodeLab = tr$tip.label) rowLinks(zy) rowLinks(x) ## 1) rowLeaf exist only in one of trees rf <- c("t1", "t3") sx <- subsetByLeaf(x = x, rowLeaf = rf) rowLinks(sx) sx <- subsetByLeaf(x = x, rowLeaf = rf, updateTree = FALSE) rowLinks(sx) ## 2) rowLeaf exist in all trees rf <- 1:3 sxx <- subsetByLeaf(x = x, rowLeaf = rf) rowLinks(sxx) ## 3) rowLeaf exist in all trees, but subset and update only the specified trees rf <- c(3:4) sxx <- subsetByLeaf(x = x, rowLeaf = rf, whichRowTree = "phylo") rowLinks(sxx)
showNode is to get nodes from the tree.
showNode(tree, only.leaf = FALSE, use.alias = FALSE)showNode(tree, only.leaf = FALSE, use.alias = FALSE)
tree |
A phylo object. |
only.leaf |
A logical value, TRUE or FALSE. The default is FALSE, all nodes are output; otherwise, leaves are output |
use.alias |
A logical value, TRUE or FALSE. The default is FALSE, and
the node label would be used to name the output; otherwise, the alias of
node label would be used to name the output. The alias of node label is
created by adding a prefix |
A vector of nodes. The numeric value is the node number, and the
vector name is the corresponding node label. If a node has no label, it
would have NA as name when use.alias = FALSE, and have the alias of
node label as name when use.alias = TRUE.
Ruizhu Huang
library(ggtree) data(tinyTree) # PLOT tree ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) ## find the node shared by provided node labels showNode(tree = tinyTree, only.leaf = TRUE, use.alias = FALSE) showNode(tree = tinyTree, only.leaf = FALSE, use.alias = FALSE)library(ggtree) data(tinyTree) # PLOT tree ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) ## find the node shared by provided node labels showNode(tree = tinyTree, only.leaf = TRUE, use.alias = FALSE) showNode(tree = tinyTree, only.leaf = FALSE, use.alias = FALSE)
joinNode is to use as few as possible nodes to represent the provided
nodes so that descendant leaves covered by the input nodes and output nodes
are exactly the same.
signalNode(tree, node, use.alias = FALSE) joinNode(tree, node, use.alias = FALSE)signalNode(tree, node, use.alias = FALSE) joinNode(tree, node, use.alias = FALSE)
tree |
A tree (phylo object) |
node |
A vector of node numbers or node labels |
use.alias |
A logical value, TRUE or FALSE. The default is FALSE, and
the node label would be used to name the output; otherwise, the alias of
node label would be used to name the output. The alias of node label is
created by adding a prefix |
A vector of nodes. The numeric value is the node number, and the
vector name is the corresponding node label. If a node has no label, it
would have NA as name when use.alias = FALSE, and have the alias of
node label as name when use.alias = TRUE.
Ruizhu Huang
data(tinyTree) library(ggtree) # PLOT tree # The node labels are in orange texts and the node numbers are in blue ggtree(tinyTree,branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) ## find the node shared by provided node labels joinNode(node = c('t4','t9'), tree = tinyTree) joinNode(node = c('t4','t9'), tree = tinyTree) joinNode(node = c('t10','Node_18', 't8'), tree = tinyTree, use.alias = FALSE) joinNode(node = c('t10','Node_18', 't8'), tree = tinyTree, use.alias = TRUE) ## find the node shared by provided node numbers joinNode(node = c(2, 3), tree = tinyTree) joinNode(node = c(2, 3, 16), tree = tinyTree)data(tinyTree) library(ggtree) # PLOT tree # The node labels are in orange texts and the node numbers are in blue ggtree(tinyTree,branch.length = 'none')+ geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) ## find the node shared by provided node labels joinNode(node = c('t4','t9'), tree = tinyTree) joinNode(node = c('t4','t9'), tree = tinyTree) joinNode(node = c('t10','Node_18', 't8'), tree = tinyTree, use.alias = FALSE) joinNode(node = c('t10','Node_18', 't8'), tree = tinyTree, use.alias = TRUE) ## find the node shared by provided node numbers joinNode(node = c(2, 3), tree = tinyTree) joinNode(node = c(2, 3, 16), tree = tinyTree)
A random phylo object created using the function rtree
tinyTreetinyTree
A phylo object with 10 tips and 9 internal nodes:
t1, t2, ..., t10.
Node_11, Node_12, ..., Node_19
toTree translates a data frame to a phylo object
toTree(data, column_order = NULL)toTree(data, column_order = NULL)
data |
A data frame or matrix. |
column_order |
A vector that includes the column names of data to
reorder columns of |
The last column is used as the leaf nodes
a phylo object
Ruizhu HUANG
library(ggtree) # Example 1: taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 4)), R3 = paste0("C", 1:5)) # Internal nodes: their labels are prefixed with colnames of taxTab # e.g., R2:B2 tree <- toTree(data = taxTab) # viz the tree ggtree(tree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint() # Example 2: duplicated rows in the 3rd and 4th rows taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 4)), R3 = c("C1", "C2", "C3", "C3", "C4")) # duplicated rows are removed with warnings tree <- toTree(data = taxTab) # Example 3: NA values in R2 column # results: the internal node with the label 'R2:' taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 2), NA, "B2"), R3 = c("C1", "C2", "C3", NA, "C4")) tree <- toTree(data = taxTab) # viz the tree ggtree(tree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint() # Example 4: duplicated values in the leaf column (R4) # Not allowed and give errors # taxTab <- data.frame(R1 = rep("A", 5), # R2 = c("B1", rep("B2", 3), "B3"), # R3 = c("C1", "C2", "C3", "C3",NA), # R4 = c("D1", "D2", "D3", NA, NA)) # Example 5: loops caused by missing values in B2-C4, B3-C4 taxTab <- data.frame(R1 = rep("A", 6), R2 = c("B1", rep("B2", 4), "B3"), R3 = c("C1", "C2", "C3", "C3", "C4", "C4"), R4 = c("D1", "D2", "D3", "D3", "D4" , "D4"), R5 = paste0("E", 1:6)) # resolove loops before run to Tree # Suffix are adding to C4 taxNew <- resolveLoop(taxTab) tree <- toTree(data = taxNew) # viz the tree ggtree(tree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint()library(ggtree) # Example 1: taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 4)), R3 = paste0("C", 1:5)) # Internal nodes: their labels are prefixed with colnames of taxTab # e.g., R2:B2 tree <- toTree(data = taxTab) # viz the tree ggtree(tree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint() # Example 2: duplicated rows in the 3rd and 4th rows taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 4)), R3 = c("C1", "C2", "C3", "C3", "C4")) # duplicated rows are removed with warnings tree <- toTree(data = taxTab) # Example 3: NA values in R2 column # results: the internal node with the label 'R2:' taxTab <- data.frame(R1 = rep("A", 5), R2 = c("B1", rep("B2", 2), NA, "B2"), R3 = c("C1", "C2", "C3", NA, "C4")) tree <- toTree(data = taxTab) # viz the tree ggtree(tree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint() # Example 4: duplicated values in the leaf column (R4) # Not allowed and give errors # taxTab <- data.frame(R1 = rep("A", 5), # R2 = c("B1", rep("B2", 3), "B3"), # R3 = c("C1", "C2", "C3", "C3",NA), # R4 = c("D1", "D2", "D3", NA, NA)) # Example 5: loops caused by missing values in B2-C4, B3-C4 taxTab <- data.frame(R1 = rep("A", 6), R2 = c("B1", rep("B2", 4), "B3"), R3 = c("C1", "C2", "C3", "C3", "C4", "C4"), R4 = c("D1", "D2", "D3", "D3", "D4" , "D4"), R5 = paste0("E", 1:6)) # resolove loops before run to Tree # Suffix are adding to C4 taxNew <- resolveLoop(taxTab) tree <- toTree(data = taxNew) # viz the tree ggtree(tree) + geom_text2(aes(label = label), color = "red", vjust = 1) + geom_nodepoint()
trackNode track nodes of a phylo tree by adding the alias labels to
them
trackNode(tree)trackNode(tree)
tree |
A phylo object |
a phylo object
Ruizhu Huang
library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue') #check whether the node number and node label are matched trackTree <- trackNode(tinyTree) ggtree(trackTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue')library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue') #check whether the node number and node label are matched trackTree <- trackNode(tinyTree) ggtree(trackTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue')
convertNode does the transformation between the number and the label of
a node on a tree
transNode(tree, node, use.alias = FALSE, message = FALSE) convertNode(tree, node, use.alias = FALSE, message = FALSE)transNode(tree, node, use.alias = FALSE, message = FALSE) convertNode(tree, node, use.alias = FALSE, message = FALSE)
tree |
A phylo object |
node |
A character or numeric vector representing tree node label(s) or tree node number(s) |
use.alias |
A logical value, TRUE or FALSE. This is an optional argument
that only requried when the input |
message |
A logical value, TRUE or FALSE. The default is FALSE. If TRUE, message will show when a tree have duplicated labels for some internal nodes. |
a vector
Ruizhu Huang
library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue') #check whether the node number and node label are matched convertNode(tinyTree, node = c(11, 2, 4, 15)) convertNode(tree = tinyTree, node = c("Node_16", "Node_11")) convertNode(tree = tinyTree, node = c("alias_16", "alias_11"))library(ggtree) data(tinyTree) ggtree(tinyTree, branch.length = 'none') + geom_text2(aes(label = label), hjust = -0.3) + geom_text2(aes(label = node), vjust = -0.8, hjust = -0.3, color = 'blue') #check whether the node number and node label are matched convertNode(tinyTree, node = c(11, 2, 4, 15)) convertNode(tree = tinyTree, node = c("Node_16", "Node_11")) convertNode(tree = tinyTree, node = c("alias_16", "alias_11"))
The class TreeSummarizedExperiment is an extension class of standard
SingleCellExperiment class. It has
four more slots that are not in
SingleCellExperiment class:
rowTree, rowLinks colTree and colLinks. The
hierarchical information of rows (columns) is stored in rowTree
(colTree) and the link between the rows (columns) of assays
tables and nodes of the tree is given in rowLinks (colLinks).
The class TreeSummarizedExperiment is designed to store
rectangular data for entities (e.g., microbes or cell types)
(assays), information about the hiearchical structure
(rowTree on rows; colTree on columns), and the mapping
information between the tree nodes and the rows or the columns of the
rectangular data. Users could provide the hiearchical structure of the
rows, columns or both) of the assays tables, and the link data will
be automatically generated in rowLinks, colData or both,
respectively. It's required that the object in rowLinks or
colLinks has the LinkDataFrame class. Please see the page
LinkDataFrame for more details.
rowTreeA phylo object or NULL. It gives information about the
hiearchical structure of rows of assays tables.
colTreeA phylo object or NULL. It gives information about the
hiearchical structure of columns of assays tables.
rowLinksA LinkDataFrame. It gives information about the link between
the nodes of the rowTree and the rows of assays tables.
colLinksA LinkDataFrame. It gives information about the link between
the nodes of the colTree and the columns of assays tables.
referenceSeqA DNAStringSet/DNAStringSetList object or
some object coercible to a DNAStringSet/DNAStringSetList
object. See DNAStringSet for
more details.
...Other slots from
SingleCellExperiment
See TreeSummarizedExperiment-constructor for constructor
functions.
See TreeSummarizedExperiment-accessor for accessor functions.
TreeSummarizedExperiment
TreeSummarizedExperiment-accessor
SingleCellExperiment
TreeSummarizedExperiment constructs a TreeSummarizedExperiment object.
TreeSummarizedExperiment( ..., rowTree = NULL, colTree = NULL, rowNodeLab = NULL, colNodeLab = NULL, referenceSeq = NULL )TreeSummarizedExperiment( ..., rowTree = NULL, colTree = NULL, rowNodeLab = NULL, colNodeLab = NULL, referenceSeq = NULL )
... |
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 |
referenceSeq |
A |
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
data("tinyTree") # the count table count <- matrix(rpois(100, 50), nrow = 10) rownames(count) <- c(tinyTree$tip.label) colnames(count) <- paste("C_", 1:10, sep = "_") # The sample information sampC <- data.frame(condition = rep(c("control", "trt"), each = 5), gender = sample(x = 1:2, size = 10, replace = TRUE)) rownames(sampC) <- colnames(count) # build a TreeSummarizedExperiment object tse <- TreeSummarizedExperiment(assays = list(count), colData = sampC, rowTree = tinyTree)data("tinyTree") # the count table count <- matrix(rpois(100, 50), nrow = 10) rownames(count) <- c(tinyTree$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)
unionLeaf list the leaf nodes that are the desendants of (at least one)
specified nodes.
unionLeaf(tree, node)unionLeaf(tree, node)
tree |
A phylo object. |
node |
A numeric or character vector. It specifies internal nodes that are changed to leaves via their node labels or numbers. |
A phylo object.
library(ggtree) data(tinyTree) ggtree(tinyTree, ladderize = FALSE) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) + geom_hilight(node = 18) + geom_point2() u1 <- unionLeaf(tree = tinyTree, node = c(19, 17)) u2 <- unionLeaf(tree = tinyTree, node = c(19, 17, 7)) (u3 <- unionLeaf(tree = tinyTree, node = c(11, 17, 7)))library(ggtree) data(tinyTree) ggtree(tinyTree, ladderize = FALSE) + geom_text2(aes(label = label), color = "darkorange", hjust = -0.1, vjust = -0.7) + geom_text2(aes(label = node), color = "darkblue", hjust = -0.5, vjust = 0.7) + geom_hilight(node = 18) + geom_point2() u1 <- unionLeaf(tree = tinyTree, node = c(19, 17)) u2 <- unionLeaf(tree = tinyTree, node = c(19, 17, 7)) (u3 <- unionLeaf(tree = tinyTree, node = c(11, 17, 7)))
TreeSummarizedExperiment objectUpdate TreeSummarizedExperiment objects to the latest version of the
class structure. This is usually called by methods in the
TreeSummarizedExperiment package rather than by users or downstream
packages.
## S4 method for signature 'TreeSummarizedExperiment' updateObject(object, ..., verbose = FALSE)## S4 method for signature 'TreeSummarizedExperiment' updateObject(object, ..., verbose = FALSE)
object |
A |
... |
additional arguments, for use in specific |
verbose |
|
An updated TreeSummarizedExperiment object