Data-adaptive testing under high-dimensions
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
R
data
docs
inst
man
paper
tests
vignettes
.Rbuildignore
.gitignore
.travis.yml
CONTRIBUTING.md
DESCRIPTION
LICENSE
Makefile
NAMESPACE
README-refs.bib
README.Rmd
README.html
README.md
_pkgdown.yml
adaptest.Rproj
appveyor.yml
codecov.yml

README.md

R/adaptest

Travis-CI Build Status AppVeyor Build Status Coverage Status Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public. GPL-2 License JOSS status

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

Authors: Wilson Cai and Nima Hejazi


What’s adaptest?

The adaptest R package is a tool for performing multiple testing on effect sizes under 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 (!("BiocManager" %in% installed.packages())) {
  install.packages("BiocManager")
}
BiocManager::install("adaptest")

To contribute, install the bleeding-edge development version 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")

Example

For details on how to best use the methyvim 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 it:

  @article{cai2018adaptest,
    doi = {},
    url = {},
    year  = {2018+},
    month = {},
    publisher = {The Open Journal},
    volume = {submitted},
    number = {},
    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}
  }

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.


License

© 2017-2018 Wilson Cai

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


References

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.