plot_ct

Convenience function for plotting crosstalkers - if you want to make more
customized/dynamic figures, there are lots of packages that can facilitate that,
including: <code>visnetwork</code>, <code>ggraph</code>, and even the base R plotting library

Provides a general toolkit for drug target identification. We include functionality to reduce large graphs to subgraphs and prioritize nodes. In addition to being optimized for use with generic graphs, we also provides support to analyze protein-protein interactions networks from online repositories. For more details on core method, refer to Weaver et al. (2021) <https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008755>.

Davis Weaver

crosstalkr

Analysis of Graph-Structured Data with a Focus on
Protein-Protein Interaction Networks

plot_ct function

<dl><dt>crosstalk_df</dt>
<dd>a dataframe containing the results of <code>compute_crosstalk</code></dd>
<dt>g</dt>
<dd>igraph network object.</dd>
<dt>label_prop</dt>
<dd>Proportion of nodes to label - based on degree</dd>
<dt>prop_keep</dt>
<dd>How many proteins do we want to keep in the visualization (as a proportion of total) -
subsets on top x proteins ranked by affinity score</dd></dl>

Arguments

Plot subnetwork identified using the compute_crosstalk function — plot_ct

<dl>

<dt>crosstalk_df</dt>
<dd>a dataframe containing the results of <code>compute_crosstalk</code></dd>


<dt>g</dt>
<dd>igraph network object.</dd>


<dt>label_prop</dt>
<dd>Proportion of nodes to label - based on degree</dd>


<dt>prop_keep</dt>
<dd>How many proteins do we want to keep in the visualization (as a proportion of total) -
subsets on top x proteins ranked by affinity score</dd>

</dl>

plot_ct: Plot subnetwork identified using the compute_crosstalk function

Description

Usage

Value

Arguments

Examples