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README.qmd
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---
format: gfm
---
[](https://doi.org/10.5281/zenodo.10046153) [](https://www.gnu.org/licenses/gpl-3.0) [](code_of_conduct.md)
# ManyEcoEvo <img src="man/figures/logo.png" align="right" width="120"/>
The `ManyEcoEvo` package provides a suite of functions for:
- Summarising, analysing and visualising the ManyEcoEvo dataset from *Gould et al.*[^1]
- Tidying and cleaning many-analyst style data for further analysis
- Reproducing the analysis in *Gould et al.* using your own many-analyst style data
[^1]: Gould, E., Fraser, H., Parker, T. *et al.* (2023). Same data, different analysts: Variation in effect sizes due to analytical decisions in ecology and evolutionary biology \[Preprint\]. Ecology and Evolutionary Biology. https://doi.org/10.32942/X2GG62
> Note that the manuscript source-code for *Gould et al.* is located in a separate repository at <https://github.com/egouldo/ManyAnalysts>, which can be viewed at <https://egouldo.github.io/ManyAnalysts/>.
## Installation
`ManyEcoEvo::` can be installed using [`devtools::`](https://devtools.r-lib.org) from GitHub with:
```{r eval=FALSE}
devtools::install_github("egouldo/ManyEcoEvo")
```
# Regenerating the ManyEcoEvo dataset
The data processing and analysis can be freely reproduced with the help of the [`targets::`](https://github.com/ropensci/targets) package. Please see the documentation at <https://docs.ropensci.org/targets/> for further detail.
Should you wish to completely reproduce the dataset generation and analysis in *Gould et al.*, complete the following steps:
1. Clone or download [https://github.com/egouldo/this repository](https://github.com/egouldo/ManyEcoEvo)
2. Run `renv::restore()` to load the packages used in the analysis pipeline locally on your machine (see [`renv::`](https://rstudio.github.io/renv/index.html) for details)
3. Run `targets::tar_destroy()` to remove any record and caches of existing targets
4. Run `targets::tar_make()` in your console, depending on the power of your machine, the analysis pipeline will take between 2 and 7 minutes to execute (plus or minus some!)
5. You can view a table of all targets in the pipeline by running `targets::tar_meta()`
6. To interact with objects or 'targets' within the analysis pipeline, call `targest::tar_load()` or `targets::tar_read()`:
```{r echo=FALSE}
suppressPackageStartupMessages(library(targets))
```
```{r}
targets::tar_read("ManyEcoEvo")
```
The script that generates datasets used in the `ManyEcoEvo::` package is located in [`ManyEcoEvo/data-raw/tar_make.R`](https://github.com/egouldo/ManyEcoEvo/blob/main/data-raw/tar_make.R).
## License
This software is licensed with the GNU GPL 3 license.
## Contributing
This package is released with a [Contributor Code of Conduct](https://github.com/egouldo/ManyEcoEvo/blob/aa2b9dcb6462f35ce873418e0b9c9697cf0b2f24/CODE_OF_CONDUCT.md).
## Citation
```
To cite package ‘ManyEcoEvo’ in publications use:
Gould E, Fraser H, Nakagawa S, Parker T (2023). _ManyEcoEvo: Meta-analyse
data from 'Many-Analysts' style studies_. R package version 1.0.0,
<https://github.com/egouldo/ManyEcoEvo>.
A BibTeX entry for LaTeX users is
@Manual{,
title = {ManyEcoEvo: Meta-analyse data from 'Many-Analysts' style studies},
author = {Elliot Gould and Hannah S. Fraser and Shinichi Nakagawa and Timothy H. Parker},
year = {2023},
note = {R package version 1.0.0},
url = {https://github.com/egouldo/ManyEcoEvo},
}
```