`R/clustering_functions.R`

`cluster_graph_vis.Rd`

Graph Visualization of Clustered Enriched Terms

```
cluster_graph_vis(
clu_obj,
kappa_mat,
enrichment_res,
kappa_threshold = 0.35,
use_description = FALSE,
vertex.label.cex = 0.7,
vertex.size.scaling = 2.5
)
```

- clu_obj
clustering result (either a matrix obtained via

`hierarchical_term_clustering`

or`fuzzy_term_clustering`

`fuzzy_term_clustering` or a vector obtained via `hierarchical_term_clustering`)- kappa_mat
matrix of kappa statistics (output of

`create_kappa_matrix`

)- enrichment_res
data frame of pathfindR enrichment results. Must-have columns are "Term_Description" (if

`use_description = TRUE`

) or "ID" (if`use_description = FALSE`

), "Down_regulated", and "Up_regulated". If`use_active_snw_genes = TRUE`

, "non_Signif_Snw_Genes" must also be provided.- kappa_threshold
threshold for kappa statistics, defining strong relation (default = 0.35)

- use_description
Boolean argument to indicate whether term descriptions (in the "Term_Description" column) should be used. (default =

`FALSE`

)- vertex.label.cex
font size for vertex labels; it is interpreted as a multiplication factor of some device-dependent base font size (default = 0.7)

- vertex.size.scaling
scaling factor for the node size (default = 2.5)

Plots a graph diagram of clustering results. Each node is an enriched term from `enrichment_res`. Size of node corresponds to -log(lowest_p). Thickness of the edges between nodes correspond to the kappa statistic between the two terms. Color of each node corresponds to distinct clusters. For fuzzy clustering, if a term is in multiple clusters, multiple colors are utilized.

```
if (FALSE) {
cluster_graph_vis(clu_obj, kappa_mat, enrichment_res)
}
```