The goal of influential is to help identification of the
most influential nodes in a network as well as the
classification and ranking of top candidate features. This package
contains functions for the classification and ranking of features,
reconstruction of networks from adjacency matrices and data frames,
analysis of the topology of the network and calculation of centrality
measures as well as a novel and powerful influential node
ranking. The Experimental data-based Integrative Ranking
(ExIR) is a sophisticated model for classification and ranking
of the top candidate features based on only the experimental data. The
first integrative method, namely the Integrated Value of
Influence (IVI), that captures all topological dimensions of
the network for the identification of network most
influential nodes is also provided as a function. Also,
neighborhood connectivity, H-index, local H-index, and collective
influence (CI), all of which required centrality measures for the
calculation of IVI, are for the first time provided in
an R package. Additionally, a function is provided for running
SIRIR model, which is the combination of leave-one-out
cross validation technique and the conventional SIR model, on a network
to unsupervisedly rank the true influence of vertices. Furthermore, 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 directions.
Check out our paper for a more complete description of the IVI formula and all of its underpinning methods and analyses.
The influential package was written by Abbas (Adrian) Salavaty
Mirana Ramialison and Peter D. Currie
You can install the official CRAN release
of the influential with the following code:
install.packages("influential")Or the development version from GitHub:
## install.packages("devtools")
devtools::install_github("asalavaty/influential",
build_vignettes = TRUE)A comprehensive introduction to influential and all of
its functions is available in the vignette.
You may browse Vignettes from within R using the following code.
browseVignettes("influential")IVI Shiny App: A shiny app for the calculation of the Integrated Value of Influence (IVI) of network nodes as well as IVI-based visualization of the network.
You can also access the IVI shiny app offline from within R and run it on your local machine using the following command.
influential::runShinyApp("IVI")You can also access the ExIR shiny app offline from within R and run it on your local machine using the following command.
influential::runShinyApp("ExIR")influentialTo cite influential, please cite its associated
paper:
You can also refer to the package’s citation information using the
citation() function.
citation("influential")Please don’t hesitate to report any bugs/issues and request for
enhancement or any other contributions. To submit a bug report or
enhancement request, please use the influential
GitHub issues tracker.