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https://github.com/pkimes/benchmark-fdr

Benchmarking study of recent covariate-adjusted FDR methods
https://github.com/pkimes/benchmark-fdr

benchmarking false-discovery-rate

Last synced: 26 days ago
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Benchmarking study of recent covariate-adjusted FDR methods

Host: GitHub
URL: https://github.com/pkimes/benchmark-fdr
Owner: pkimes
License: mit
Created: 2017-08-19T18:37:27.000Z (over 7 years ago)
Default Branch: master
Last Pushed: 2019-04-16T23:59:22.000Z (over 5 years ago)
Last Synced: 2024-02-15T11:33:27.582Z (10 months ago)
Topics: benchmarking, false-discovery-rate
Language: Jupyter Notebook
Homepage:
Size: 23.4 MB
Stars: 14
Watchers: 9
Forks: 5
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

Awesome-Bioinformatics-Benchmarks - available on GitHub - shiny). The source code, ExperimentHub package, and Shiny application are all made available under the MIT license. (Statistics / False Discovery Rates)

README

# Benchmarking Study of Covariate-Adjusted FDR Methods

This repository includes all code used to perform analyses and generate figures for the manuscript, [_A practical guide to methods controlling false discoveries in computational biology_](https://www.biorxiv.org/content/early/2018/10/31/458786).

## Notes

Before attempting to run the code in this repository, please read the following notes.

### Cloning

We **do not** recommond cloning this entire repository. The repository includes all historical commits and is incredibly large. Instead, we recommend either making a shallow clone of the repository using the following code.

```bash
git clone --depth=1 https://github.com/pkimes/benchmark-fdr.git
```

### SummarizedBenchmark

The code in this repository was run using an older version of the `SummarizedBenchmark` package and will not run with newer versions of the package. An older version of the package should be installed from GitHub using the following R code.

```r
devtools::install_github("areyesq89/SummarizedBenchmark", ref = "fdrbenchmark")
```

### Rendered reports

Final rendered `Rmd` files for simulations and case studies included in the manuscripts are available in [this repository](https://github.com/pkimes/benchmark-fdr-html), and are rendered [here](http://www.pkimes.com/benchmark-fdr-html/) via GitHub pages.

## Citation

Korthauer K†, Kimes PK†, Duvallet C‡, Reyes A‡, Subramanian A‡, Teng M, Shukla C, Alm EJ, Hicks SC\*.
_A practical guide to methods controlling false discoveries in computational biology._ bioRxiv. doi: https://doi.org/10.1101/458786

†: co-first authors, ‡: co-second authors, \*: corresponding author

## License/Copyright
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![License: CC BY-NC-ND 4.0](https://img.shields.io/badge/License-CC%20BY--NC--ND%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by-nc-nd/4.0/)
All code in this project is made available under a MIT license.
All non-code text in this project is made available under a CC BY-NC-ND 4.0 license.