Connect to WFP's Moda platform to R, download data, and obtain the list of individuals with access to the project along with their access level.

Provides a consistent interface for connecting R to various 
    data sources including file systems and databases. 
    Designed for clinical research, 'connector' streamlines access to 'ADAM', 
    'SDTM' for example. It helps to deal with multiple data formats through a standardized API and centralized 
    configuration.

Expands the 'connector' <https://github.com/NovoNordisk-OpenSource/connector> package and provides a convenient
    interface for accessing and interacting with 'Databricks' <https://www.databricks.com> volumes and
    tables directly from R.

A collection of helper functions and 'htmlwidgets' to help publishers
    curate content collections on 'Posit Connect'. The components,
    Card, Grid, Table, Search, and Filter can be used to produce a
    showcase page or gallery contained within a static or interactive
    R Markdown page.

Collects several different methods for analyzing and
    working with connectivity data in R.  Though primarily oriented towards
    marine larval dispersal, many of the methods are general and useful for
    terrestrial systems as well.

The congeneric normal-ogive model is a popular model for 
   psychometric data (McDonald, R. P. (1997) <doi:10.1007/978-1-4757-2691-6_15>).
   This model estimates the model, calculates theoretical and concrete 
   reliability coefficients, and predicts the latent variable of the model. 
   This is the companion package to Moss (2020) <doi:10.31234/osf.io/nvg5d>.

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.