Description Usage Arguments Value Examples
View source: R/network_plots.R
xina_plot_bycluster is to draw protein-protein interaction network plots of each cluster
1 2 3 4 5 6 7 8 | xina_plot_bycluster(xina_result, clustering_result, cl = NULL,
condition = "all", flag_legend = TRUE, centrality_type = NULL,
flag_simplify = TRUE, layout_specified = "",
vertex_label_flag = TRUE, vertex.label.dist = 0.6,
vertex.label.cex = 0.8, edge.arrow.size = 0.4, vertex.size = 10,
vertex.shape = "sphere", vertex.color = "",
edge.color = "darkgray", legend_location = "bottom",
flag_unknown_only = FALSE)
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xina_result |
A list containing XINA network analysis results. See xina_analysis | |||||||||||||||||
clustering_result |
A list containing XINA clustering results. See xina_clustering | |||||||||||||||||
cl |
Cluster number in the XINA clustering results | |||||||||||||||||
condition |
Default is 'all', which means use all the proteins to draw graphs. If you specify the experimental condition name used for XINA clustering, | |||||||||||||||||
flag_legend |
If it is TRUE, a legend will be printed out together. | |||||||||||||||||
centrality_type |
'centrality_type' should be one of c('Degree', 'Eigenvector', 'Hub', 'Authority', 'Closeness', 'Betweenness')
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flag_simplify |
If it is TRUE (default), XINA will exclude unconnected proteins | |||||||||||||||||
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_
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 | |||||||||||||||||
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 | |||||||||||||||||
vertex.color |
Color of nodes. Default is pink. | |||||||||||||||||
edge.color |
Color of edges. Default is pink. | |||||||||||||||||
legend_location |
If centrality_type is chosen, xina_plot_single add 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'. | |||||||||||||||||
flag_unknown_only |
If this is TRUE, 'xina_plot_bycluster' will plot proteins that do not have any protein-protein interaction in the given database |
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
PNG images of PPI network plots of all the clusters
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## 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)
# plot cluster #1
xina_plot_bycluster(xina_result_example, example_clusters, cl=1)
# plot PPI network of Control condition in cluster #1
xina_plot_bycluster(xina_result_example, example_clusters, cl=1, condition='Control')
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