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# PERK

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## Description

`PERK` is an R package containing a tool (Shiny App) to predict and
visualize environmental concentration and risk using pharmaceutical
prescription data collected at fine spatial resolution.

The tool helps users to input their measured concentration, to compare
the predicted (PEC) and measured concentrations (MEC) of the
pharmaceuticals by means of the PEC/MEC ratio, to establish whether the
predicted equations used tend to underestimate or overestimate measured
values.

It provides a consistent interactive user interface in a familiar
dashboard layout, enabling users to visualise predicted values and
compare with their measured values without any hassles. Users can
download data and graphs generated using the tool in .csv or publication
ready images.

## Getting started

Although the main purpose of the R package is to be installed and used
locally, you can give it a quick [online test
run](http://51.141.234.162/shiny/DemoPERK/) to determine whether it’s
right for you before installing it. With just 3 commands, you can
install it and begin using it if you like what you see:

``` r
install.packages('PERK')
library('PERK')
run_app()
```

For an introduction to the package, step-by-step instructions on getting
started, and more information on the different ways you can use the
package
[*PERK-Walkthrough*](https://jkkishore85.github.io/PERK/articles/PERK-Walkthrough.html)
tutorial.

You can install the development version of `PERK` from GitHub through
following command.

``` r
install.packages("remotes")
library(remotes)
install_github("jkkishore85/PERK")
```

## Citation and Contributors

Please cite this article from this
[Preprint](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4306129)
if the package helps you with your work in any way that justifies it.

This work is a part of the Wastewater Fingerprinting for Public Health
Assessment (ENTRUST) project funded by Wessex Water and EPSRC IAA (grant
no. EP/R51164X/1).

## Disclaimer

We accept no liability for any errors in the data or its publication
here. Use this data at your own risk.
