Plot a ConsortiumMetabolismSet object

Render the dendrogram of a ConsortiumMetabolismSet's hierarchical clustering of consortia, optionally annotated with the internal cluster identifiers used by extractCluster.

Usage

# S4 method for class 'ConsortiumMetabolismSet,ANY'
plot(
  x,
  label_colours = NULL,
  max_nodes = 20,
  label_size = 3,
  showClusterIds = TRUE
)

Arguments

x

A ConsortiumMetabolismSet object.

label_colours

Optional tibble with label and colour columns mapping consortium names to custom tip colours.

max_nodes

Integer. Maximum number of internal cluster nodes to overlay with cluster-ID badges (only used when showClusterIds = TRUE). Defaults to 20.

label_size

Numeric tip-label size.

showClusterIds

Logical. If TRUE (default), draw the internal cluster identifiers used by extractCluster as small filled circles on top of the dendrogram. Set to FALSE for a clean dendrogram suitable for figure export.

Value

A ggplot object (returned invisibly).

Details

The dendrogram is the one computed at CMS construction time from the FOS overlap matrix; tip labels are consortium names.

When showClusterIds = TRUE (the default), small numbered circles overlay the internal nodes of the dendrogram (up to max_nodes of them). The numbers are the cluster IDs that extractCluster accepts to retrieve a sub-CMS for the subtree rooted at that node.

For figure export, set showClusterIds = FALSE to obtain a clean dendrogram without the cluster-ID overlays. Use label_colours to recolour individual tip labels by supplying a tibble with label and colour columns (one row per consortium to recolour).

See also

extractCluster

Examples

cm1 <- synCM("comm_1", n_species = 3, max_met = 5)
cm2 <- synCM("comm_2", n_species = 4, max_met = 6)
cms <- ConsortiumMetabolismSet(cm1, cm2, name = "test")
#> 
#> ── Creating CMS "test" ─────────────────────────────────────────────────────────
#> ℹ Validating 2 <ConsortiumMetabolism> objects
#> ✔ Validating 2 <ConsortiumMetabolism> objects [10ms]
#> 
#> ℹ Collecting metabolites from 2 consortia
#> ✔ Collecting metabolites from 2 consortia [28ms]
#> 
#> ℹ Re-indexing 6 unique metabolites
#> ✔ Re-indexing 6 unique metabolites [24ms]
#> 
#> ℹ Expanding 2 binary matrices to 6-dimensional space
#> ✔ Expanding 2 binary matrices to 6-dimensional space [21ms]
#> 
#> ℹ Computing 6 x 6 levels matrix
#> ✔ Computing 6 x 6 levels matrix [23ms]
#> 
#> ℹ Computing pairwise overlap (1 pairs via crossprod)
#> ✔ Computing pairwise overlap (1 pairs via crossprod) [21ms]
#> 
#> ℹ Assembling pathway data from 2 consortia
#> ✔ Assembling pathway data from 2 consortia [28ms]
#> 
#> ℹ Building dendrogram from 2 x 2 dissimilarity matrix
#> ✔ Building dendrogram from 2 x 2 dissimilarity matrix [20ms]
#> 
#> ℹ Extracting dendrogram node positions
#> ✔ Extracting dendrogram node positions [22ms]
#> 
#> ℹ Collecting 2 consortium graphs
#> CMS "test" created: 2 consortia, 6 metabolites (0.2s)
#> ✔ Collecting 2 consortium graphs [76ms]
#> 
plot(cms)

plot(cms, showClusterIds = FALSE)