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Travis-CI Build Status AppVeyor Build Status Coverage Status Project Status: Active – The project has reached a stable, usable state and is being actively developed. BioC status Bioc Time Bioc Downloads GPL-2 License Zenodo DOI JOSS Status and DOI

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).


For standard use, install from Bioconductor using BiocManager:

if (!requireNamespace("BiocManager", quietly=TRUE)) {

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


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

    doi = {10.21105/joss.00161},
    url = {},
    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}

    url = {},
    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.”

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.