mem2emap: Convert multiEnrichMap mem output to EnrichmentMap emap
In jmw86069/jamenrich: Analysis and Visualization of Multiple Gene Set Enrichments

mem2emap

R Documentation

Convert multiEnrichMap mem output to EnrichmentMap emap

Description

Convert multiEnrichMap mem output to EnrichmentMap emap

Usage

mem2emap(
  mem,
  overlap = 0.2,
  p_cutoff = mem$p_cutoff,
  min_count = 4,
  colorV = mem$colorV,
  cluster_function = igraph::cluster_walktrap,
  cluster_list = NULL,
  num_keep_terms = 3,
  keep_terms_sep = ",\n",
  repulse = 3.3,
  remove_singlets = TRUE,
  color_by_nodes = FALSE,
  apply_direction = TRUE,
  direction_max = 2,
  direction_floor = 0.5,
  do_plot = TRUE,
  ...
)

Arguments

`mem`	`list` object output from `multiEnrichMap()`
`overlap`	`numeric` value between 0 and 1 indicating the Jaccard overlap coefficient required between any two pathways in order to create a network edge connecting these two pathways. Typically, `overlap=0.2` is default, which specifies roughly 20% overlap in genes shared between two pathway nodes. Note these genes must be involved in enrichment, and therefore does not use all possible genes annotated to a pathway. Therefore connections are only created with enriched genes are shared between pathways.
`p_cutoff`	`numeric` threshold used for significant enrichment P-value, usually defined in the `mem` object.
`min_count`	`integer` threshold for minimum genes involved in enrichment in order for a pathway to be considered significant during this analysis.
`colorV`	`character` vector of R colors used for each enrichment.
`cluster_function`	`function` used to cluster nodes in the resulting `igraph` object, used to help generate a visual summary.
`num_keep_terms`	`integer` number of terms to keep from each pathway cluster, when `cluster_function` is supplied above. Common terms are removed from each pathway cluster, then remaining terms are sorted by decreasing occurrence, and used as a straightforward summary of pathways in each cluster.
`keep_terms_sep`	`character` string used to separated multiple pathway terms defined by `num_keep_terms` above.
`repulse`	`numeric` value passed to `layout_with_qfr()`.
`remove_singlets`	`logical` indicating whether to remove pathway singlets, which have no connections to any other pathways. It can help simplify busy figures, however removing a singlet pathway is not recommended because it may imply the pathways were not statistically significant, and in fact they were.
`color_by_nodes`	`logical` indicating whether to colorize pathway clusters based upon blending the node colors within each cluster. Note that a mix of colors often turns brown, so this feature has unpredictable benefit.
`do_plot`	`logical` indicating whether to render the resulting plot.
`...`	additional arguments are passed to `jam_igraph()` to customize the network plot.

Details

This function is currently In development.

This function is intended to convert mem output from multiEnrichMap() into an EnrichmentMap igraph format which represents the statistical enrichment support from each pathway enrichment.

This function can apply P-value thresholds using the input mem, or using a custom value.

A node clustering function is applied by default, which may help define suitable subgroups of nodes. When defined, the clusters are used to define nodegroups for edge bundling.

Other jam igraph functions: cnet2df(), cnet2im(), cnetplotJam(), cnetplot_internalJam(), color_edges_by_nodegroups(), color_edges_by_nodes_deprecated(), color_edges_by_nodes(), color_nodes_by_nodegroups(), communities2nodegroups(), drawEllipse(), edge_bundle_bipartite(), edge_bundle_nodegroups(), enrichMapJam(), fixSetLabels(), flip_edges(), get_bipartite_nodeset(), igraph2pieGraph(), jam_igraph(), jam_plot_igraph(), label_communities(), layout_with_qfrf(), layout_with_qfr(), memIM2cnet(), mem_multienrichplot(), nodegroups2communities(), rectifyPiegraph(), relayout_with_qfr(), removeIgraphBlanks(), removeIgraphSinglets(), reorderIgraphNodes(), rotate_igraph_layout(), spread_igraph_labels(), subgraph_jam(), subsetCnetIgraph(), subset_igraph_components(), sync_igraph_communities(), with_qfr()