Clustering unilayer and multilayer network data by means of finite mixtures is the main utility of netClust.

Facilitates network clustering and evaluation of cluster
        configurations.

Create interactive analytic networks. It joins the data analysis power of R to obtain coincidences, co-occurrences and correlations, and the visualization libraries of 'JavaScript' in one package.

Infer system functioning with empirical NETwork COMparisons. These methods are part of a growing paradigm in network science that uses relative comparisons of networks to infer mechanistic classifications and predict systemic interventions. They have been developed and applied in Langendorf and Burgess (2021) <doi:10.1038/s41598-021-99251-7>, Langendorf (2020) <doi:10.1201/9781351190831-6>, and Langendorf and Goldberg (2019) <doi:10.48550/arXiv.1912.12551>.

The 'NetCoupler' algorithm identifies potential direct effects of 
    correlated, high-dimensional variables formed as a network with an external 
    variable. The external variable may act as the dependent/response variable 
    or as an independent/predictor variable to the network.

Implementation of the NetCutter algorithm described in
    Müller and Mancuso (2008) <doi:10.1371/journal.pone.0003178>. The package
    identifies co-occurring terms in a list of containers. For example, it
    may be used to detect genes that co-occur across genomes.

Implementation of discriminant analysis with network structures in predictors accommodated to do classification and prediction.

Empirical statistical analysis, visualization and simulation of
    diffusion and contagion processes on networks. The package implements algorithms
    for calculating network diffusion statistics such as transmission rate, hazard
    rates, exposure models, network threshold levels, infectiousness (contagion),
    and susceptibility. The package is inspired by work published in Valente,
    et al., (2015) <DOI:10.1016/j.socscimed.2015.10.001>; Valente (1995) <ISBN:
    9781881303213>, Myers (2000) <DOI:10.1086/303110>, Iyengar and others (2011)
    <DOI:10.1287/mksc.1100.0566>, Burt (1987) <DOI:10.1086/228667>; among others.