Data-adaptive statistics for multiple testing in high-dimensional biology
Authors: Wilson Cai and Nima Hejazi
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).
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”).
For details on how to best use the adaptest R package, please consult
the most recent package
vignette
available through the Bioconductor
project.
If you encounter any bugs or have any specific feature requests, please file an issue.
Contributions are very welcome. Interested contributors should consult our contribution guidelines prior to submitting a pull request.
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},
title = {{adaptest}: Data-Adaptive Statistics for High-Dimensional
Testing in {R}},
journal = {The Journal of Open Source Software}
}
@article{cai2018+adaptive,
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}
}
The development of this software was supported in part through grants from the National Institutes of Health: P42 ES004705-29 and T32 LM012417-02.
© 2017-2018 Wilson Cai
The software contents of this repository are distributed under the GPL-2
license. See file LICENSE for details.
Cai, Weixin, Nima S Hejazi, and Alan E Hubbard. n.d. “Data-Adaptive Statistics for Multiple Hypothesis Testing in High-Dimensional Settings.” https://arxiv.org/abs/1704.07008.
Hubbard, Alan E, Sara Kherad-Pajouh, and Mark J van der Laan. 2016. “Statistical Inference for Data Adaptive Target Parameters.” The International Journal of Biostatistics 12 (1): 3–19.