Clustering on Network of Samples

Wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. 'Conos' focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes. This package interacts with data available through the 'conosPanel' package, which is available in a 'drat' repository. To access this data package, see the instructions at < https://github.com/kharchenkolab/conos>. The size of the 'conosPanel' package is approximately 12 MB.

Import and Analyse Ego-Centered Network Data

Tools for importing, analyzing and visualizing ego-centered network data. Supports several data formats, including the export formats of 'EgoNet', 'EgoWeb 2.0' and 'openeddi'. An interactive (shiny) app for the intuitive visualization of ego-centered networks is provided. Also included are procedures for creating and visualizing Clustered Graphs (Lerner 2008 ).

Structural Equation Modeling and Confirmatory Network Analysis

Multi-group (dynamical) structural equation models in combination with confirmatory network models from cross-sectional, time-series and panel data . Allows for confirmatory testing and fit as well as exploratory model search.

Fit, Simulate and Diagnose Models for Network Evolution Based on Exponential-Family Random Graph Models

An integrated set of extensions to the 'ergm' package to analyze and simulate network evolution based on exponential-family random graph models (ERGM). 'tergm' is a part of the 'statnet' suite of packages for network analysis. See Krivitsky and Handcock (2014) and Carnegie, Krivitsky, Hunter, and Goodreau (2015) .

Fit, Simulate and Diagnose Exponential-Family Models for Multiple or Multilayer Networks

A set of extensions for the 'ergm' package to fit multilayer/multiplex/multirelational networks and samples of multiple networks. 'ergm.multi' is a part of the Statnet suite of packages for network analysis. See Krivitsky, Koehly, and Marcum (2020) and Krivitsky, Coletti, and Hens (2023) .

Network Analysis for Omics Data

Comprehensive network analysis package. Calculate correlation network fastly, accelerate lots of analysis by parallel computing. Support for multi-omics data, search sub-nets fluently. Handle bigger data, more than 10,000 nodes in each omics. Offer various layout method for multi-omics network and some interfaces to other software ('Gephi', 'Cytoscape', 'ggplot2'), easy to visualize. Provide comprehensive topology indexes calculation, including ecological network stability.

Extracts the Backbone from Networks

An implementation of methods for extracting a sparse unweighted network (i.e. a backbone) from an unweighted network (e.g., Hamann et al., 2016 ), a weighted network (e.g., Serrano et al., 2009 ), or a weighted projection (e.g., Neal et al., 2021 ).

Modeling and Inferring Gene Networks

Analyzes gene expression (time series) data with focus on the inference of gene networks. In particular, GeneNet implements the methods of Schaefer and Strimmer (2005a,b,c) and Opgen-Rhein and Strimmer (2006, 2007) for learning large-scale gene association networks (including assignment of putative directions).

Biological and Chemical Data Networks

Data Package that includes several examples of chemical and biological data networks, i.e. data graph structured.

Network Dynamic Temporal Visualizations

Renders dynamic network data from 'networkDynamic' objects as movies, interactive animations, or other representations of changing relational structures and attributes.