_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-influential 2.3.1
Propagated dependencies: r-tibble@3.3.1 r-seuratobject@5.4.0 r-rcpp@1.1.1-1.1 r-ranger@0.18.0 r-matrix@1.7-5 r-janitor@2.2.1 r-irlba@2.3.7 r-igraph@2.3.1 r-ggplot2@4.0.3 r-foreach@1.5.2 r-edger@4.10.0 r-doparallel@1.0.17 r-cli@3.6.6
Channel: guix-cran
Location: guix-cran/packages/i.scm (guix-cran packages i)
Home page: https://github.com/asalavaty/influential
Licenses: GPL 3
Build system: r
Synopsis: Identification and Classification of the Most Influential Nodes
Description:

This package provides functions for the identification, classification, and ranking of influential nodes and candidate features from network and omics data. The package implements the Integrated Value of Influence (IVI) for integrative network centrality analysis, the SIR-based Influence Ranking (SIRIR) model for unsupervised influence ranking, and the Experimental data-based Integrative Ranking (ExIR) model for prioritizing candidate driver, biomarker, and mediator features from experimental omics data. Functions are provided for network reconstruction from adjacency matrices and data frames, topological analysis, centrality calculation, assessment of associations between centrality measures, and conditional probability analysis. ExIR supports bulk and single-cell omics data, including matrices, sparse matrices, data frames, tibbles, and Seurat objects.

Total packages: 1