xina_plot_single {XINA} | R Documentation

## xina_plot_single

### Description

xina_plot_single draws protein-protein interaction network plot for given 'protein_list'.

### Usage

    xina_plot_single(xina_result, protein_list, centrality_type = NULL,
      layout_specified = "", vertex_label_flag = TRUE, main = NULL,
      vertex.label.color = "black", vertex.color = NA,
      edge.color = "darkgray", vertex.label.dist = 0.6,
      vertex.label.cex = 0.8, edge.arrow.size = 0.4, vertex.size = 10,
      vertex.shape = "sphere", legend_location = "bottom",
      num_breaks = 5, digits_round_up = 5, flag_simplify = TRUE,
      flag_legend = TRUE)

### Arguments

`xina_result` | A list containing XINA network analysis results. See xina_analysis
`protein_list` | A vector of gene names to draw a protein-protein interaction network graph.
`centrality_type` | 'centrality_type' should be one of c('Degree', 'Eigenvector', 'Hub', 'Authority', 'Closeness', 'Betweenness')
Centrality score | igraph function
Degree | degree
Eigenvector | eigen_centrality
Hub | hub_score
Authority | authority_score
Closeness | closeness
Betweenness | betweenness
`layout_specified` | This can change network layout. 'layout_specified' should be one of c('sphere', 'star', 'gem', 'tree', 'circle', 'random', 'nicely'). XINA's layouts are based on igraph's layout. See layout_
Layout | igraph layout name
sphere | layout_on_sphere
star | layout_as_star
gem | layout_with_gem
tree | layout_as_tree
circle | layout_in_circle
random | layout_randomly
nicely | layout_nicely
Default is 'layout_nicely' of igraph
`vertex_label_flag` | If vertex_label_flag is TRUE (default), igraph network graphs will be labeled by gene names If vertex_label_flag is FALSE, igraph network graphs will be drawn without labels
`main` | Title of network figure. IF it is NULL (default), it will be the number of plotted proteins
`vertex.label.color` | Color of labels. Default is black
`vertex.color` | Color of nodes. Default is pink.
`edge.color` | Color of edges. Default is pink.
`vertex.label.dist` | Distance between node and label. Default is 0.6
`vertex.label.cex` | Size of labels Default is 0.8
`edge.arrow.size` | Size of edges Default is 0.4
`vertex.size` | Size of nodes Default is 10
`vertex.shape` | You can choose node shape. Default is 'sphere'. See shapes
`legend_location` | If centrality_type is chosen, 'xina_plot_single' adds the color legend guiding rank of nodes based on the centrality score. Default is 'bottomright', but you can choose one of these 'bottomright', 'bottom', 'bottomleft', 'left', 'topleft', 'top', 'topright', 'right' and 'center'.
`num_breaks` | 'num_breaks' is the number of ranks based on network centrality. Default is 5.
`digits_round_up` | See Round
`flag_simplify` | If it is TRUE (default), XINA will exclude unconnected proteins
`flag_legend` | If it is TRUE, a legend will be printed out together.

### Value

A PNG file (XINA_Cluster_Networks.png) displaying protein-protein interaction network plots of all the clusters and a list containing XINA network analysis results

### Examples

    ## the following code is to show how it works quickly
    ## load XINA example data
    data(xina_example)

    ## load the previously processed XINA analysis results
    # if you want to learn how to run 'xina_analysis', please see \link[XINA]{xina_analysis}
    data(xina_result_example)

    # get gene names that are clustered to #21 in "Stimulus2" condition
    subgroup <- subset(example_clusters$aligned, Stimulus2==21)
    protein_list <- subgroup$`Gene name`

    # Calculate protein-protein interaction network
    xina_plot_single(xina_result_example, protein_list)

    # Calculate protein-protein interaction network and Eigenvector centrality
    eigen_info <- xina_plot_single(xina_result_example, protein_list, centrality_type='Eigenvector')

[Package XINA version 1.6.0 Index]