Enables users to build 'ToxPi' prioritization models and provides 
  functionality within the grid framework for plotting ToxPi graphs.
  'toxpiR' allows for more customization than the 'ToxPi GUI' 
  (<https://toxpi.github.io/>) and integration into existing workflows for greater 
  ease-of-use, reproducibility, and transparency.
  toxpiR package behaves nearly identically to the GUI; the package 
  documentation includes notes about all differences.
  The vignettes download example files from 
  <https://github.com/ToxPi/ToxPi-example-files>.

A 'shiny' app that generates plots and summary tables from repeat-dose
        toxicology study results to facilitate holistic evaluation of the drug safety of 
        active pharmaceutical ingredients (API) prior to initiation of clinical trials.

Contains logic for single sample gene set testing of cancer transcriptomic data with adjustment for normal tissue-specificity.
  Frost, H. Robert (2023) "Tissue-adjusted pathway analysis of cancer (TPAC)" <doi:10.1101/2022.03.17.484779>.

Contains summary data on gene expression in normal human tissues from the Human Protein Atlas for use with the 
  Tissue-Adjusted Pathway Analysis of cancer (TPAC) method.
  Frost, H. Robert (2023) "Tissue-adjusted pathway analysis of cancer (TPAC)" <doi:10.1101/2022.03.17.484779>.

Tools for estimating and inferring two-way partial area under receiver operating characteristic curves (two-way pAUC), partial area under receiver operating characteristic curves (pAUC), and partial area under ordinal dominance curves (pODC). Methods includes Mann-Whitney statistic and Jackknife, etc.

Constraint-based causal discovery using the PC algorithm while
    accounting for a partial node ordering, for example a partial temporal ordering
    when the data were collected in different waves of a cohort study.
    Andrews RM, Foraita R, Didelez V, Witte J (2021) <arXiv:2108.13395>  
    provide a guide how to use tpc to analyse cohort data.

Tools to calculate trait probability density functions (TPD) at
    any scale (e.g. populations, species, communities). TPD functions are used to compute
    several indices of functional diversity, as well as its partition across scales.
    These indices constitute a unified framework that incorporates the underlying
    probabilistic nature of trait distributions into uni- or multidimensional
    functional trait-based studies. See Carmona et al. (2016) <doi:10.1016/j.tree.2016.02.003> for
    further information.