CINNA1.2.2 package

Deciphering Central Informative Nodes in Network Analysis

calculate_centralities

Centrality measure calculation

dangalchev_closeness_centrality

Dangalchev Closeness Centrality

giant_component_extract

Giant component extraction of a graph

graph_extract_components

Component extraction of a graph

group_centrality

Group Centrality

harmonic_centrality

Harmonic Centrality

local_bridging_centrality

Local Bridging Centrality

misc_extract_components

Component extraction of miscellaneous graph formats

pca_centralities

PCA Centrality Measures

proper_centralities

Proper centrality measure representation

summary_calculate_centralities

Summarize centrality measure calculation results

summary_graph_extract_components

Summarize component extraction of a graph

summary_pca_centralities

Summarize PCA result related to centrality measures

summary_tsne_centralities

Summarize t-Distributed Stochastic Neighbor Embedding (t-SNE) on centr...

tsne_centralities

t-Distributed Stochastic Neighbor Embedding (t-SNE) on centrality meas...

visualize_association

Pairwise association plot between centrality measures

visualize_correlations

Correlation plot between centrality measures

visualize_dendrogram

Dendrogram plot among centrality measures

visualize_graph

Graph visualization based on a specific centrality measure

visualize_heatmap

Heatmap plot between centrality measures

visualize_pair_correlation

Pairwise correlation plot between two centrality measures

wiener_index_centrality

Wiener Index Centrality

Download source packageRead PDF manual

Computing, comparing, and demonstrating top informative centrality measures within a network. "CINNA: an R/CRAN package to decipher Central Informative Nodes in Network Analysis" provides a comprehensive overview of the package functionality Ashtiani et al. (2018) <doi:10.1093/bioinformatics/bty819>.

  • Maintainer: Minoo Ashtiani
  • License: GPL-3
  • Last published: 2023-08-08