compute_dnp

This function takes a tidy dataframe as input containing RNA sequencing data for one or more samples and conducts in-silico repression.
Make sure to run with the same arguments for ppi and cache to maintain consistency for a given pipeline.

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

compute_dnp function

<dl><dt>cache</dt>
<dd>user-provided filepath for where to store data etc</dd>
<dt>df</dt>
<dd>dataframe output of compute_np</dd>
<dt>experiment_name</dt>
<dd>name of the experiment for saving output.</dd>
<dt>ppi</dt>
<dd>should we use biogrid or stringdb for the PPI</dd>
<dt>ncores</dt>
<dd>number of cores to use for calculations</dd>
<dt>min_score</dt>
<dd>if ppi is stringdb, which mininum score should we use to filter edges?</dd></dl>

Arguments

main function to compute delta np for every gene in a given dataframe - assumes compute_np has already been run for a given dataset — compute_dnp

<dl>

<dt>cache</dt>
<dd>user-provided filepath for where to store data etc</dd>


<dt>df</dt>
<dd>dataframe output of compute_np</dd>


<dt>experiment_name</dt>
<dd>name of the experiment for saving output.</dd>


<dt>ppi</dt>
<dd>should we use biogrid or stringdb for the PPI</dd>


<dt>ncores</dt>
<dd>number of cores to use for calculations</dd>


<dt>min_score</dt>
<dd>if ppi is stringdb, which mininum score should we use to filter edges?</dd>

</dl>

compute_dnp: main function to compute delta np for every gene in a given dataframe - assumes compute_np has already been run for a given dataset

Description

Usage

Value

Arguments