grnPlot {eegc} | R Documentation

## Gene Regulatory Network Plot

### Description

This function plot the a cell/tissue-specific gene regulatory network with genes in the five categories, alterntively reducing the network size by plotting given specific genes as nodes.

### Usage

    grnPlot(grn.data, cate.gene, filter = TRUE, nodes = NULL, centrality.score,
    col = NULL, main= NULL, vertex.label =NULL, vertex.label.dist = 0, vertex.label.font = 1,
    vertex.label.cex = 0.5, vertex.label.color="black", edge.arrow.size = 0.4,
    edge.color = "grey", layout ="layout_with_lgl", legend.labels = NULL, ...)

### Arguments

`grn.data` | a data frame with two columns named "TF" and "TG" to specify the genes as transcription regulators (TF) and target genes being regulated (TG).
`cate.gene` | a list of the five gene categories as nodes in the network, alternatively output by `categorizeGene`.
`filter` | logical to specify if the network is reduced to less nodes by a filter, logical to `TRUE` for a clear visualization.
`nodes` | a character vector of genes to kept in the network, only applied when `filter` is `TRUE`.
`centrality.score` | a vector or data frame of centrality scores for genes in the network, alternatively calculated by `networkAnalyze` function.
`col` | colors of gene vertex in each `cate.gene`.
`main` | title of the plot.
`vertex.label, vertex.label.dist, vertex.label.font, vertex.label.cex, vertex.label.color` | parameters for vertex labels, to specify the labels of vertex, the position of labels on the vertex, font size, cex and color for label, see details in `igraph.plotting`.
`edge.arrow.size, edge.color` | parameters for edge to specify the arrow size and color of edge, see details in `igraph.plotting`.
`layout` | the layout of network plot, see details in `layout`.
`legend.labels` | vector of label names for each `cate.gene`.
`...` | other parameters used in `igraph.plotting`.

### Value

a igraph plot for gene regulatory network.

### Examples

    ## Not run:
      # select genes to shown their regulation with others
      node.genes = c("ZNF641", "BCL6")
      # enlarge the centrality
      centrality.score = degree$centrality*100
      names(centrality.score) = degree$Gene
      par(mar = c(2,2,3,2))
      grnPlot(grn.data = human.grn[[tissue]], cate.gene = cate.gene, filter = TRUE,
             nodes = node.genes, centrality.score = centrality.score,
             main = "Gene regulatory network")

    ## End(Not run)

[Package eegc version 1.10.0 Index]