Plotting tree information enriched with information

Source: R/AllGenerics.R, R/plotTree.R

Based on the stored data in a TreeSummarizedExperiment a tree can be plotted. From the rowData, the assays as well as the colData information can be taken for enriching the tree plots with additional information.

plotRowTree(x, ...)

plotColTree(x, ...)

# S4 method for class 'TreeSummarizedExperiment'
plotColTree(x, tree.name = "phylo", ...)

# S4 method for class 'TreeSummarizedExperiment'
plotRowTree(x, tree.name = "phylo", ...)

Arguments

x

a TreeSummarizedExperiment.

...

additional arguments for plotting.

  • layout: layout for the plotted tree. See ggtree for details.

  • relabel.tree: Logical scalar. Should the tip labels be relabelec using the output of getTaxonomyLabels(x, with_rank = TRUE)? (Default: FALSE)

  • order.tree: Logical scalar. Should the tree be ordered based on alphabetic order of taxonomic levels? (Default: FALSE)

  • levels.rm: Logical scalar. Should taxonomic level information be removed from labels? (Default: FALSE)

  • show.label, show.highlights, show.highlight.label, abbr.label logical vector, integer vector. or character vector. If a logical scalar is given, should tip labels be plotted or if a logical vector is provided, which labels should be shown? If an integer or character vector is provided, it will be converted to a logical vector. The integer values must be in the range of 1 and number of nodes, whereas the values of a character vector must match values of the label column in the node data. In case of a character vector only values corresponding to actual labels will be plotted and if no labels are provided no labels will be shown. (Default: FALSE)

  • add.legend: Logical scalar. Should legends be plotted? (Default: TRUE)

  • edge.colour.by: Character scalar. Specification of a column metadata field or a feature to colour tree edges by. (Default: NULL)

  • edge.size.by: Character scalar. Specification of a column metadata field or a feature to size tree edges by. (Default: NULL)

  • colour.by: Character scalar. Specification of a column metadata field or a feature to colour tree nodes by. (Default: NULL)

  • shape.by: Character scalar. Specification of a column metadata field or a feature to shape tree nodes by. (Default: NULL)

  • size.by: Character scalar. Specification of a column metadata field or a feature to size tree tips by. (Default: NULL)

  • show.tips: Logical scalar. Whether to show tip points. (Default: FALSE)

  • show.nodes: Logical scalar. Whether to show node points. (Default: FALSE)

  • colour.highlights.by: Logical scalar. Should the highlights be colour differently? If show.highlights = TRUE, colour_highlights will be set to TRUE as default. (Default: FALSE)

  • assay.type: Character scalar. Specifies which assay to obtain expression values from, for use in point aesthetics. (Default: "counts")

  • other.fields: Character vector. Additional fields to include in the node information without plotting them. (Default: NULL)

tree.name

Character scalar. Specifies a rowTree/colTree from x. (Default: tree.name = "phylo")

Value

a ggtree plot

Details

If show.label or show.highlight.label have the same length as the number of nodes, the vector will be used to relabel the nodes.

Examples

library(scater)
library(mia)
# preparation of some data
data(GlobalPatterns)
GlobalPatterns <- agglomerateByRanks(GlobalPatterns)
altExp(GlobalPatterns,"Genus") <- addPerFeatureQC(
    altExp(GlobalPatterns,"Genus"))
rowData(altExp(GlobalPatterns,"Genus"))$log_mean <- log(
    rowData(altExp(GlobalPatterns,"Genus"))$mean)
rowData(altExp(GlobalPatterns,"Genus"))$detected <- rowData(
    altExp(GlobalPatterns,"Genus"))$detected / 100
top_genus <- getTop(
    altExp(GlobalPatterns,"Genus"),
    method = "mean",
    top = 100L,
    assay.type = "counts"
)
#
x <- altExp(GlobalPatterns,"Genus")
plotRowTree(
    x[rownames(x) %in% top_genus,],
    tip.colour.by = "log_mean", tip.size.by = "detected"
)


# plot with tip labels
plotRowTree(
    x[rownames(x) %in% top_genus,],
    tip.colour.by = "log_mean",
    tip.size.by = "detected",
    show.label = TRUE
)

# plot with selected labels
labels <- c("Genus:Providencia", "Genus:Morganella", "0.961.60")
plotRowTree(
    x[rownames(x) %in% top_genus,],
    tip.colour.by = "log_mean",
    tip.size.by = "detected",
    show.label = labels,
    layout = "rectangular"
)


# plot with labeled edges
plotRowTree(
    x[rownames(x) %in% top_genus,],
    edge.colour.by = "Phylum",
    tip.colour.by = "log_mean"
)

# if edges are sized, colours might disappear depending on plotting device
plotRowTree(
    x[rownames(x) %in% top_genus,],
    node.colour.by = "Phylum",
    edge.size.by = "detected",
    edge.colour.by = "log_mean"
)


# aggregating data over the taxonomic levels for plotting a taxonomic tree
# please note that the original tree of GlobalPatterns is dropped by
# unsplitByRanks
altExps(GlobalPatterns) <- splitByRanks(GlobalPatterns)
top_phyla <- getTop(
    altExp(GlobalPatterns,"Phylum"),
    method = "mean",
    top = 10L,
    assay.type="counts"
)
altExps(GlobalPatterns) <- lapply(altExps(GlobalPatterns), addPerFeatureQC)
altExps(GlobalPatterns) <- lapply(
    altExps(GlobalPatterns), function(y){
        rowData(y)$log_mean <- log(rowData(y)$mean)
        rowData(y)$detected <- rowData(y)$detected / 100
        return(y)
    })
x <- unsplitByRanks(GlobalPatterns)
x <- addHierarchyTree(x)
#> Warning: The root is added with label 'ALL'

highlights <- c(
    "Phylum:Firmicutes","Phylum:Bacteroidetes",
    "Family:Pseudomonadaceae","Order:Bifidobacteriales")
plotRowTree(
    x[rowData(x)$Phylum %in% top_phyla,],
    tip.colour.by = "log_mean",
    node.colour.by = "log_mean",
    show.highlights = highlights,
    show.highlight.label = highlights,
    colour.highlights.by = "Phylum"
)
#> Warning: some tip numbers were larger than the number of tips: they were ignored
#> Warning: 537 row(s) are dropped due to mismatch with nodes of 'value'


# If you do not want to show internal nodes
plotRowTree(
    x[rowData(x)$Phylum %in% top_phyla,],
    edge.colour.by = "Phylum",
    edge.size.by = "detected",
    node.colour.by = "log_mean",
    show.nodes = FALSE
)
#> Warning: some tip numbers were larger than the number of tips: they were ignored
#> Warning: 537 row(s) are dropped due to mismatch with nodes of 'value'