A comprehensive suite of functions designed for constructing
    and managing 'ShinyItemAnalysis' modules, supplemented with detailed
    guides, ready-to-use templates, linters, and tests. This package
    allows developers to seamlessly create and integrate one or more
    modules into their existing packages or to start a new module project
    from scratch.

Fits bi-variate ellipses to stable isotope data using Bayesian
    inference with the aim being to describe and compare their isotopic
    niche.

Provides models to identify bimodally expressed genes from
 RNAseq data based on the Bimodality Index. SIBERG models the  RNAseq data in
 the finite mixture modeling framework and incorporates mechanisms  for
 dealing with RNAseq normalization. Three types of mixture models are
 implemented,  namely, the mixture of log normal, negative binomial, or 
 generalized Poisson distribution. See Tong et al. (2013)
 <doi:10.1093/bioinformatics/bts713>.

Aims to quantify time intensity data by using sigmoidal and
    double sigmoidal curves. It fits straight lines, sigmoidal, 
    and double sigmoidal curves on to time vs intensity data. 
    Then all the fits are used to make decision on which model 
    best describes the data. This method was first developed 
    in the context of single-cell viral growth analysis (for
    details, see Caglar et al. (2018) <doi:10.7717/peerj.4251>),
    and the package name stands for "SIngle CEll Growth Analysis in R".

Fetch data on targeted public investments from Plataforma +Brasil (SICONV) <http://plataformamaisbrasil.gov.br/>, 
    the responsible system for requests, execution, and monitoring of federal discretionary transfers in Brazil.

The code computes the structural intervention distance (SID) between a true directed acyclic graph (DAG) and an estimated DAG. Definition and details about the implementation can be found in J. Peters and P. Bühlmann: "Structural intervention distance (SID) for evaluating causal graphs", Neural Computation 27, pages 771-799, 2015  <doi:10.1162/NECO_a_00708>.