Data-adaptive statistics for multiple testing in high-dimensional biology

Authors: Wilson Cai and Nima Hejazi

## What’s adaptest?

The adaptest R package is a tool for performing multiple testing on effect sizes in high-dimensional settings, using the approach of data-adaptive statistical target parameters and inference. For technical details on the data-adaptive multiple testing procedure, consult Cai, Hejazi, and Hubbard (n.d.). For an introduction to statistical inference procedures using data-adaptive target parameters, the interested reader is directed to Hubbard, Kherad-Pajouh, and van der Laan (2016).

## Installation

For standard use, install from Bioconductor using BiocManager:

if (!requireNamespace("BiocManager", quietly=TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("adaptest")

To contribute, install the development version (i.e., branch master) from GitHub via devtools:

devtools::install_github("wilsoncai1992/adaptest")

Current and prior Bioconductor releases are available under branches with numbers prefixed by “RELEASE_”. For example, to install the version of this package available via Bioconductor 3.7, use

devtools::install_github("wilsoncai1992/adaptest", ref = "RELEASE_3_7")

Note: As the first stable release of this package was through Bioconductor v3.7, the minimum version of R required to install adaptest is 3.5.0 (codename “Joy in Playing”).

## Example

For details on how to best use the adaptest R package, please consult the most recent package vignette available through the Bioconductor project.

## Issues

If you encounter any bugs or have any specific feature requests, please file an issue.

## Contributions

Contributions are very welcome. Interested contributors should consult our contribution guidelines prior to submitting a pull request.

## Citation

After using the adaptest R package, please cite the following

  @article{cai2018adaptest,
doi = {10.21105/joss.00161},
url = {https://doi.org/10.21105/joss.00161},
year  = {2018},
month = {October},
publisher = {The Open Journal},
volume = {3},
number = {30},
author = {Cai, Weixin and Hubbard, Alan E and Hejazi, Nima S},
Testing in {R}},
journal = {The Journal of Open Source Software}
}

url = {https://arxiv.org/abs/1704.07008},
year  = {2018+},
author = {Cai, Weixin and Hejazi, Nima S and Hubbard, Alan E},
title = {Data-adaptive statistics for multiple hypothesis testing in
high-dimensional settings}
}

## Funding

The development of this software was supported in part through grants from the National Institutes of Health: P42 ES004705-29 and T32 LM012417-02.

The software contents of this repository are distributed under the GPL-2 license. See file LICENSE for details.