Plotting tree information enriched with information

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(object, ...)

plotColTree(object, ...)

# S4 method for TreeSummarizedExperiment
plotColTree(
  object,
  tree_name = "phylo",
  relabel_tree = FALSE,
  order_tree = FALSE,
  remove_levels = FALSE,
  show_label = FALSE,
  show_highlights = FALSE,
  show_highlight_label = FALSE,
  abbr_label = FALSE,
  add_legend = TRUE,
  layout = "circular",
  edge_colour_by = NULL,
  edge_size_by = NULL,
  tip_colour_by = NULL,
  tip_shape_by = NULL,
  tip_size_by = NULL,
  node_colour_by = NULL,
  node_shape_by = NULL,
  node_size_by = NULL,
  colour_highlights_by = NULL,
  by_exprs_values = "counts",
  other_fields = list(),
  ...
)

# S4 method for TreeSummarizedExperiment
plotRowTree(
  object,
  tree_name = "phylo",
  relabel_tree = FALSE,
  order_tree = FALSE,
  remove_levels = FALSE,
  show_label = FALSE,
  show_highlights = FALSE,
  show_highlight_label = FALSE,
  abbr_label = FALSE,
  add_legend = TRUE,
  layout = "circular",
  edge_colour_by = NULL,
  edge_size_by = NULL,
  tip_colour_by = NULL,
  tip_shape_by = NULL,
  tip_size_by = NULL,
  node_colour_by = NULL,
  node_shape_by = NULL,
  node_size_by = NULL,
  colour_highlights_by = NULL,
  by_exprs_values = "counts",
  other_fields = list(),
  ...
)

Arguments

object: a TreeSummarizedExperiment object.
...: additional arguments for plotting. See mia-plot-args for more details i.e. call help("mia-plot-args")
tree_name: a single character value specifying a rowTree/colTree from object. (By default: tree_name = "phylo")
relabel_tree: logical scalar, Should the tip labels be relabeled using the output of getTaxonomyLabels(object, with_rank = TRUE)? (default: relabel_tree = FALSE)
order_tree: logical scalar, Should the tree be ordered based on alphabetic order of taxonomic levels? (default: order_tree = FALSE)
remove_levels: logical scalar, Should taxonomic level information be removed from labels? (default: relabel_tree = FALSE)
show_label, show_highlights, show_highlight_label, abbr_label: logical (scalar), integer 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: add_legend = TRUE)
layout: layout for the plotted tree. See ggtree for details.
edge_colour_by: Specification of a column metadata field or a feature to colour tree edges by, see the by argument in ?retrieveCellInfo for possible values.
edge_size_by: Specification of a column metadata field or a feature to size tree edges by, see the by argument in ?retrieveCellInfo for possible values.
tip_colour_by: Specification of a column metadata field or a feature to colour tree tips by, see the by argument in ?retrieveCellInfo for possible values.
tip_shape_by: Specification of a column metadata field or a feature to shape tree tips by, see the by argument in ?retrieveCellInfo for possible values.
tip_size_by: Specification of a column metadata field or a feature to size tree tips by, see the by argument in ?retrieveCellInfo for possible values.
node_colour_by: Specification of a column metadata field or a feature to colour tree nodes by. Must be a field from other_fields.
node_shape_by: Specification of a column metadata field or a feature to shape tree nodes by. Must be a field from other_fields.
node_size_by: Specification of a column metadata field or a feature to size tree nodes by. Must be a field from other_fields.
colour_highlights_by: Should the highlights be colour differently? If show_highlights = TRUE, colour_highlights will be set to TRUE as default. (default: colour_highlights = FALSE)
by_exprs_values: A string or integer scalar specifying which assay to obtain expression values from, for use in point aesthetics - see the exprs_values argument in ?retrieveCellInfo.
other_fields: Additional fields to include in the node information without plotting them.

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)
#> Loading required package: scuttle
library(mia)
# preparation of some data
data(GlobalPatterns)
altExps(GlobalPatterns) <- splitByRanks(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 <- getTopFeatures(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,],
            edge_colour_by = "Phylum",
            edge_size_by = "detected",
            tip_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 <- getTopFeatures(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
              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")


plotRowTree(x[rowData(x)$Phylum %in% top_phyla,],
            edge_colour_by = "Phylum",
            edge_size_by = "detected",
            tip_colour_by = "log_mean",
            node_colour_by = "log_mean")

Plotting tree information enriched with information

Arguments

Value

Details

See also

Examples