labelClusters {NAIR} | R Documentation |
Label Clusters in a Network Graph Plot
Description
Functions for labeling the clusters in network graph plots with their cluster IDs. The user can specify a cluster-level property by which to rank the clusters, labeling only those clusters above a specified rank.
Usage
labelClusters(
net,
plots = NULL,
top_n_clusters = 20,
cluster_id_col = "cluster_id",
criterion = "node_count",
size = 5, color = "black",
greatest_values = TRUE
)
addClusterLabels(
plot,
net,
top_n_clusters = 20,
cluster_id_col = "cluster_id",
criterion = "node_count",
size = 5,
color = "black",
greatest_values = TRUE
)
Arguments
net |
A |
plots |
Specifies which plots in |
plot |
A |
top_n_clusters |
A positive integer specifying the number of clusters to label. Those with the
highest rank according to the |
cluster_id_col |
Specifies the column of |
criterion |
Can be used to specify a cluster-level network property by which to rank the
clusters. Non-default values are ignored unless |
size |
The font size of the cluster ID labels. Passed to the |
color |
The color of the cluster ID labels. Passed to the |
greatest_values |
Logical. Controls whether clusters are ranked according to the greatest or
least values of the property specified by the |
Details
The list net
must contain the named elements
igraph
(of class igraph
),
adjacency_matrix
(a matrix
or
dgCMatrix
encoding edge connections),
and node_data
(a data.frame
containing node metadata),
all corresponding to the same network. The lists returned by
buildRepSeqNetwork()
and
generateNetworkObjects()
are examples of valid inputs for the net
argument.
Value
labelClusters()
returns a copy of net
with the specified plots
annotated.
addClusterLabels()
returns an annotated copy of plot
.
Author(s)
Brian Neal (Brian.Neal@ucsf.edu)
References
Hai Yang, Jason Cham, Brian Neal, Zenghua Fan, Tao He and Li Zhang. (2023). NAIR: Network Analysis of Immune Repertoire. Frontiers in Immunology, vol. 14. doi: 10.3389/fimmu.2023.1181825
See Also
addClusterMembership()
,
getClusterStats()
,
generateNetworkGraphPlots()
Examples
set.seed(42)
toy_data <- simulateToyData()
network <- buildRepSeqNetwork(
toy_data, "CloneSeq",
cluster_stats = TRUE,
color_nodes_by = "cluster_id",
color_scheme = "turbo",
color_legend = FALSE,
plot_title = NULL,
plot_subtitle = NULL,
size_nodes_by = 1
)
network <- labelClusters(network)
network$plots$cluster_id