Graph Visualization of Clustered Enriched Terms

```
cluster_graph_vis(
clu_obj,
kappa_mat,
enrichment_res,
kappa_threshold = 0.35,
use_description = FALSE
)
```

## Arguments

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` ) |

## Value

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.

## Examples

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