Welcome to the SAIGE-BRUSH documentation!

SAIGE-Biobank Re-Usable SAIGE Helper (SAIGE-BRUSH) is an implementation of the popular SAIGE GWAS software. Fully containerized and ready for use without installation or any code handling. Submit your configuration file and the rest is done.


Good news! There is no installation required to use this pipeline and it should be OS agnostic. There are only 2 true system dependencies and most HPCs and shared resources already have these dependencies installed:

  • Singularity version >= 3.0

  • Golang version >= go1.13.5 (has been tested on versions go1.13.5 and go1.15.2 on a Linux OS).

If not, you can install Singularity and install Golang using the links on your local computer. Both should be available across OS platforms for Windows, MacOS, and Linux.

If you haven’t visited our github repository, please do so by visiting the SAIGE-BRUSH github repo. The repo has all the information on how to access the executable and pull down the container.

Full Pipeline Overview



See also

Need more help? Please submit any questions or bugs to the SAIGE-BRUSH github issues page


The most important acknowledgment is for the group of developers, investigaters, scientists, and researchers of SAIGE . This pipline is honestly just an automated wrapper to most of their work. They have an excellent github page here at https://github.com/weizhouUMICH/SAIGE – The entire team is very responsive to github questions. They are tirelessy working on newer and more complex versions of SAIGE, and for that I must thank them. It is an amazing piece of software! Please read their publication:

Zhou, W., Nielsen, J. B., Fritsche, L. G., Dey, R., Gabrielsen, M. E., Wolford, B. N., LeFaive, J., VandeHaar, P., Gagliano, S. A., Gifford, A., Bastarache, L. A., Wei, W. Q., Denny, J. C., Lin, M., Hveem, K., Kang, H. M., Abecasis, G. R., Willer, C. J., & Lee, S. (2018). Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. Nature genetics, 50(9), 1335–1341. https://doi.org/10.1038/s41588-018-0184-y

All of this work could not be done without the full support of the Colorado Center for Personalized Medicine (CCPM) under the guidance of their Biobank, and the Translation Informatics Services (TIS) sector, among several input from exerpienced scientists and professor within CCPM whose expertise is in GWAS.