centrality.measures

The centrality measures of a co-expression network of lncRNAs and
mRNAs in lung adenocarcinoma

datasets

Contains functions for reconstruction of networks from
adjacency matrices and data frames, analysis of the topology of the network
and calculation of centrality measures, and identification of the most
influential nodes (network hubs). Also, some functions have been provided
for the assessment of dependence and correlation of two network centrality
measures as well as the conditional probability of deviation from their
corresponding means in opposite direction.
Fred Viole and David Nawrocki (2013, ISBN:1490523995).

Adrian Salavaty

influential

Identification of the Most Influential Nodes (Hubs)

centrality.measures function

A data frame with 794 rows and 4 variables:<dl class="dl-horizontal">
 <dt>BetweennessCentrality</dt><dd>Betweenness Centrality</dd>
 <dt>Degree</dt><dd>Degree Centrality</dd>
 <dt>name</dt><dd>Node (gene) name</dd>
 <dt>NeighborhoodConnectivity</dt><dd>Neighborhood Connectivity</dd>
 ...
</dl>

Format

Centrality measures dataset — centrality.measures

A data frame with 794 rows and 4 variables:<dl class='dl-horizontal'>
 <dt>BetweennessCentrality</dt><dd>Betweenness Centrality</dd>
 <dt>Degree</dt><dd>Degree Centrality</dd>
 <dt>name</dt><dd>Node (gene) name</dd>
 <dt>NeighborhoodConnectivity</dt><dd>Neighborhood Connectivity</dd>
 ...
</dl>

centrality.measures: Centrality measures dataset

Description

Usage

Arguments

Format