Multi-generational pedigree inference from incomplete data on
    hundreds of SNPs, including parentage assignment and sibship clustering.
    See Huisman (2017) (<DOI:10.1111/1755-0998.12665>) for more information.

Apache Drill is a low-latency distributed query engine designed to enable 
    data exploration and analysis on both relational and non-relational data stores, 
    scaling to petabytes of data. Methods are provided that enable working with Apache 
    Drill instances via the REST API, DBI methods
    and using 'dplyr'/'dbplyr' idioms. Helper functions are included to facilitate
    using official Drill Docker images/containers.

Enables reading and writing binary and ASCII data to 
             RS232/RS422/RS485 or any other virtual serial interface of the
             computer.

Infrastructure for ordering objects with an implementation of several
    seriation/sequencing/ordination techniques to reorder matrices, dissimilarity
    matrices, and dendrograms. Also provides (optimally) reordered heatmaps,
    color images and clustering visualizations like dissimilarity plots, and
    visual assessment of cluster tendency plots (VAT and iVAT). Hahsler et al (2008) <doi:10.18637/jss.v025.i03>.

Calculate and compare lower confidence bounds for binomial series system reliability. The R 'shiny' application, launched by the function launch_app(), weaves together a workflow of customized simulations and delta coverage calculations to output recommended lower confidence bound methods.

Translates antibody levels measured in cross-sectional population samples into estimates of the frequency with which seroconversions (infections) occur in the sampled populations. Replaces the previous 'seroincidence' package. Methods originally published in Simonsen et al. (2009) <doi:10.1002/sim.3592> and Teunis et al. (2012) <doi:10.1002/sim.5322>, and further developed in subsequent publications by de Graaf et al. (2014) <doi:10.1016/j.epidem.2014.08.002>, Teunis et al. (2016) <doi:10.1016/j.epidem.2016.04.001>, and Teunis et al. (2020) <doi:10.1002/sim.8578>.