README.Rmd

---
output: github_document
---

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

# DataTidyGelaDURT

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The goal of DataTidyGelaDURT is to provide easy, documented access to the datasets analysed in [Effects of BCG vaccination on donor unrestricted T cells in two prospective cohort studies (Gela, 2022)](https://doi.org/10.1016/j.ebiom.2022.103839). The companion project, [`ReportGelaDURT`](/~https://github.com/SATVILab/ReportGelaDURT), analyses the data and produces the paper figures.

Due to privacy concerns, raw data are not publicly available. Please email Thomas Scriba at `thomas.scriba@uct.ac.za` should you require access.

Note that the package has been updated since the paper was published, and the version at the time of publication is available [as a GitHub release](/~https://github.com/SATVILab/DataTidyGelaDURT/releases/tag/v1.0.0).

## Installation

To install the latest version of `DataTidyGelaDURT` from [GitHub](/~https://github.com/), run the following:

``` r
if (!requireNamespace("remotes", quietly = TRUE)) install.packages("remotes")
remotes::install_github("SATVILab/DataTidyGelaDURT")
```

To install the version of `DataTidyGelaDURT` as when submitted for final publication, run the following:

``` r
if (!requireNamespace("remotes", quietly = TRUE)) install.packages("remotes")
remotes::install_github("SATVILab/DataTidyGelaDURT@v1.0.0")
```

## Data sets

The following datasets are available:
```{r , results = "asis", echo = FALSE}
data_tbl <- tibble::tibble(
  Dataset = c(
    "data_tidy_clin_adult", "data_tidy_clin_infant", "data_tidy_freq",
    "data_tidy_freq_ifng", "data_tidy_hladr_adult",
    "data_tidy_hladr_infant", "data_tidy_mem"
  )
)
pander::pandoc.table(data_tbl)
```

Use `?DataTidyGelaDURT::<dataset_name>` to see documentation for each dataset.

CSV versions of the data are available inside `inst/extdata/`. Once installed, the following R code will give the path to the CSV files: `system.file("extdata", package = "DataTidyGelaDURT")`.

## Project structure

The data are processed using `Rmd` files inside `data-raw/`.