Reproducible and automated analysis of multiplex bead assays such
    as CBA (Morgan et al. 2004; <doi: 10.1016/j.clim.2003.11.017>), LEGENDplex
    (Yu et al. 2015; <doi: 10.1084/jem.20142318>), and MACSPlex (Miltenyi
    Biotec 2014; Application note: Data acquisition and analysis without the
    MACSQuant analyzer;
    <https://www.miltenyibiotec.com/upload/assets/IM0021608.PDF>). The
    package provides functions for streamlined reading of fcs files, and
    identification of bead clusters and analyte expression. The package eases
    the calculation of standard curves and the subsequent calculation of the
    analyte concentration.

A minimalist web framework for developing application programming 
    interfaces in R that provides a flexible framework for handling common 
    HTTP-requests, errors, logging, and an ability to integrate any R code as 
    server middle-ware.

A bootstrap-based approach to integrate multiple forms of
    high dimensional genomic data with multiple clinical endpoints.  This method
    is used to find clinically meaningful groups of genomic features, such
    as genes or pathways. A manuscript describing this method is in preparation.

Plots univariate comparison graphs, an alternative to
        boxplot/stripchart/violin plot.

These data contain morphological image measurements for dried
    beans from Koklu and Ozkan (2020) <doi:10.1016/j.compag.2020.105507>.

It is vital to assess the heterogeneity of treatment effects
    (HTE) when making health care decisions for an individual patient or a group
    of patients. Nevertheless, it remains challenging to evaluate HTE based
    on information collected from clinical studies that are often designed and
    conducted to evaluate the efficacy of a treatment for the overall population.
    The Bayesian framework offers a principled and flexible approach to estimate
    and compare treatment effects across subgroups of patients defined by their
    characteristics. This package allows users to explore a wide range of Bayesian
    HTE analysis models, and produce posterior inferences about HTE. See Wang et al.
    (2018) <DOI:10.18637/jss.v085.i07> for further details.