addGraphLabels: Label Nodes in a Network Graph Plot

In mlizhangx/Network-Analysis-for-Repertoire-Sequencing-: Network Analysis of Immune Repertoire

Label Nodes in a Network Graph Plot

Description

Functions for annotating a graph plot to add custom labels to the nodes.

Usage

labelNodes(
  net,
  node_labels,
  plots = NULL,
  size = 5,
  color = "black"
)

addGraphLabels(
  plot,
  node_labels,
  size = 5,
  color = "black"
)

Arguments

net	A list of network objects conforming to the output of buildRepSeqNetwork() or generateNetworkObjects(). See details.
plot	A ggraph object containing the network graph plot.
node_labels	A vector containing the node labels, where each entry is the label for a single node. The length should match the number of nodes in the plot.
plots	Specifies which plots in net$plots to annotate. Accepts a character vector of element names or a numeric vector of element position indices. The default NULL annotates all plots.
size	The font size of the node labels. Passed to the size argument of geom_node_text().
color	The color of the node labels. Passed to the size argument of geom_node_text().

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.

Labels are added using geom_node_text().

Value

labelNodes() returns a copy of net with the specified plots annotated.

addGraphLabels() returns a ggraph object containing the original plot annotated with the node labels.

Author(s)

Brian Neal ([e-mail])

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

Webpage for the NAIR package

Examples

set.seed(42)
toy_data <-
  simulateToyData(
    samples = 1,
    sample_size = 10,
    prefix_length = 1
  )

# Generate network
network <-
  buildNet(
    toy_data,
    seq_col = "CloneSeq",
    plot_title = NULL,
    plot_subtitle = NULL
  )

# Label each node with its receptor sequence
network <- labelNodes(network, "CloneSeq", size = 3)

network$plots[[1]]

mlizhangx/Network-Analysis-for-Repertoire-Sequencing- documentation built on April 7, 2024, 12:02 p.m.