README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

library(lockr)
```

# lockr

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## Overview

`lockr` is a user-friendly R package designed for encrypting/decrypting files, with the aim of facilitating the storage and sharing of research compendiums using R.

The creation of this package was inspired by Ben Marwick, Carl Boettiger & Lincoln Mullen's article [Packaging Data Analytical Work Reproducibly Using R (and Friends)](https://doi.org/10.1080/00031305.2017.1375986).

## Prerequisites

To use the main functions of `lockr`, some familiarity with the [R programming language](https://www.r-project.org/) is required.

If you are not comfortable with R, we strongly recommend checking out Hadley Wickham and Garrett Grolemund's free online book [R for Data Science](https://r4ds.had.co.nz/), as well as the Coursera course [Data Science: Foundations using R](https://www.coursera.org/specializations/data-science-foundations-r) from John Hopkins University (free for audit students).

## Installation

You can install `lockr` using:

``` {r, eval = FALSE}
# install.packages("remotes")
remotes::install_github("giperbio/lockr")
```

## Citation

If you use `lockr` in your research, please consider citing it. We have put a lot of work into building and maintaining this free and open-source R package. The citation can be found below.

```{r}
citation("lockr")
```

## Contributing

We welcome contributions, including bug reports.

Please take a moment to review our [Guidelines for Contributing](https://giperbio.github.io/lockr/CONTRIBUTING.html).

<br>

Become a supporter of `lockr`!

Click [here](https://github.com/sponsors/danielvartan) to make a donation. Please indicate the `lockr` package in your donation message.