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Code for the ideel hackathon. Based on OJs arms repo but will some key changes

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Research compendium for antimalarial resistance risk mapping

This is a working R compendium (think R package but for reproducible analysis). A good overview on research compendiums, see the R for Reproducible Research course.

Installation

git clone https://github.com/OJWatson/arms.git
cd arms
open arms.Rproj

Next, if renv has been used in this repository (look out for renv.lock) then use renv::restore to set up package dependencies. Otherwise devtools::install_dev_deps() will install all required packages, as specified in the Imports in DESCRIPTION.

Overview

The structure within analysis is as follows:

R/                            # Packaged R functions 

analysis/
    |
    ├── 01_xxxxx /            # analysis scripts used for generating figures
    |
    ├── plots/                # location of figures produced by the analysis scripts
    |
    ├── tables/               # location of any tables produced by the analysis scripts
    |
    ├── data_raw/             # data obtained from elsewhere and treated read-only    
    |
    ├── data_derived/         # intermediate data generated during the analysis
    |
    ├── data_out/             # data outputs produced for external partners

Any analysis scripts with “X_” in the name are used to format raw data shared with us for this project that could not be included in the repository and only summaries of the data as needed for the modelling could be included. These scripts are still included to show how the raw data was processed and the summaries saved in data_raw for use later on. In this way, we ensure transparency and reproducibility.

Analysis scripts are to be run in the numbered order they are included. If there are shared numbers, then any order of those scripts works.

Compendium DOI:

https://zenodo.org/record/XXX

The files at the URL above will generate the results as found in the publication.

The R package

This repository is organized as an R package. There are only a few R functions exported in this package - the majority of the R code is in the analysis directory. The R package structure is here to help manage dependencies, to take advantage of continuous integration, and so we can keep file and data management simple. For any R packages that are used frequently in this repository, they are documented in R/ and are used in the analysis folder using devtools::load_all().

To download the package source as you see it on GitHub, for offline browsing, use this line at the shell prompt (assuming you have Git installed on your computer):

git clone https://github.com/OJWatson/arms.git

Once the download is complete, open the arms.Rproj in RStudio to begin working with the package and compendium files. We will endeavour to keep all package dependencies required listed in the DESCRIPTION.

In addition, once analysis is completed, we will use renv to track package dependencies for reproducibility. Please use renv::restore to restore the state of the project and see https://rstudio.github.io/renv/articles/renv.html for more information.

Licenses

Code: MIT year: 2023, copyright holder: OJ Watson

Data: CC-0 attribution requested in reuse

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