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.

A toolbox to handle and represent trophic networks in space or time across aggregation levels. This package contains a layout algorithm specifically designed for trophic networks, using dimension reduction on a diffusion graph kernel and trophic levels. Importantly, this package provides a layout method applicable for large trophic networks.

Given a CSV file with titles and abstracts, the package creates a
    document-term matrix that is lemmatized and stemmed and can directly be used to
    train machine learning methods for automatic title-abstract screening in the
    preparation of a meta analysis.

Novel method to unbiasedly include studies with Non-statistically Significant Unreported Effects (NSUEs) in a meta-analysis. First, the function calculates the interval where the unreported effects (e.g., t-values) should be according to the threshold of statistical significance used in each study. Afterward, the method uses maximum likelihood techniques to impute the expected effect size of each study with NSUEs, accounting for between-study heterogeneity and potential covariates. Multiple imputations of the NSUEs are then randomly created based on the expected value, variance, and statistical significance bounds. Finally, it conducts a restricted-maximum likelihood random-effects meta-analysis separately for each set of imputations, and it performs estimations from these meta-analyses. Please read the reference in 'metansue' for details of the procedure.

The canonical way to perform meta-analysis involves using effect sizes.
   When they are not available this package provides a number of methods for
   meta-analysis of significance values including the methods of Edgington, Fisher,
   Lancaster, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results;
   and routines for graphical display.