null_score

Calculation of diffusion null scores for each node

Designed for network analysis, leveraging the personalized PageRank algorithm to calculate node scores in a given graph. This innovative approach allows users to uncover the importance of nodes based on a customized perspective, making it particularly useful in fields like bioinformatics, social network analysis, and more.

Farzaneh Firoozbakht

DiffNet

Identifying Significant Node Scores using Network Diffusion
Algorithm

null_score function

<dl><dt>graph</dt>
<dd>an igraph object with the length of N</dd>
<dt>initial.score</dt>
<dd>a named vector of node preferences of length N served as the initial values for diffusion algorithm.</dd>
<dt>damping</dt>
<dd>The damping factor of the diffusion algorithm.</dd>
<dt>N.repeat</dt>
<dd>number of permutation repeats of null scores.</dd>
<dt>n.cores</dt>
<dd>number of cores for parallel processing.</dd></dl>

Arguments

Calculation of diffusion null scores for each node — null_score

<dl>

<dt>graph</dt>
<dd>an igraph object with the length of N</dd>


<dt>initial.score</dt>
<dd>a named vector of node preferences of length N served as the initial values for diffusion algorithm.</dd>


<dt>damping</dt>
<dd>The damping factor of the diffusion algorithm.</dd>


<dt>N.repeat</dt>
<dd>number of permutation repeats of null scores.</dd>


<dt>n.cores</dt>
<dd>number of cores for parallel processing.</dd>

</dl>

null_score: Calculation of diffusion null scores for each node

Description

Usage

Value

Arguments

Details

Examples