plot.PCSFe: Plot an interactive subnetwork with functional enrichment...
In murodzhon/PCSF: Network-based interpretation of highthroughput data

Description Usage Arguments Details Author(s) References See Also Examples

plot.PCSFe plots an interactive figure of the subnetwork to display the functionla enrichment analysis, which is obtained by employing enrichment_analysis on the subnetwork.

1
2
3

## S3 method for class 'PCSFe'
plot(x, edge_width = 5, node_size = 30,
  node_label_cex = 1, ...)

`x`	An output subnetwork provided by the `enrichment_analysis`. It is "PCSFe" object derived from an igraph class, and it has the edge cost and vertex prize attributes.
`edge_width`	A `numeric` value to emphasize the maximum edge width. A default value is 5. This value must be greater than 1.
`node_size`	A `numeric` value to emphasize the maximum node size. A default value is 30. This value must be greater than 10.
`node_label_cex`	A `numeric` value to set the node label size. A default value is 1.
`...`	Ignored.

An enrichment analysis of the final subnetwork obtained by multiple runs of the PCSF (with random noise added edge costs) is performed by using enrichment_analysis. The subnetwork is clustered using an edge betweenness clustering algorithm from the igraph package, and for each cluster functional enrichment is done by employing the ENRICHR API (Chen et al., 2013). An interactive visualization of the final subnetwork is plotted, where the node sizes and edge widths are proportional to the frequency of show ups in total randomised runs. Nodes are colored according to the cluster membership, and the top 15 functional enrichment terms are displayed in tabular format during the hover-over of the node in that cluster. A specific cluster can be displayed separately in the figure by selecting from the icon list at the top left side of the figure.

Murodzhon Akhmedov

Chen E.Y., Christopher M.T., Yan K., Qiaonan D., Zichen W., Gabriela V.M., Neil R.C., and Avi M. (2013) Enrichr: Interactive and Collaborative Html5 Gene List Enrichment Analysis Tool. BMC Bioinformatics 14 (1). BioMed Central: 1.

enrichment_analysis, PCSF_rand, plot.PCSF

## Not run: 
library("PCSF")
data("STRING")
data("Tgfb_phospho")
terminals <- Tgfb_phospho
ppi <- construct_interactome(STRING)
subnet <- PCSF_rand(ppi, terminals, n = 10, r = 0.1, w = 2, b = 1, mu = 0.0005)
res <- enrichment_analysis(subnet)
plot(res$subnet)
## End(Not run)