Performs the O2PLS data integration method for two datasets yielding joint and data-specific parts for each dataset.
The algorithm automatically switches to a memory-efficient approach to fit O2PLS to high dimensional data.
It provides a rigorous and a faster alternative cross-validation method to select the number of components,
as well as functions to report proportions of explained variation and to construct plots of the results.
See the software article by el Bouhaddani et al (2018)
Welcome to the OmicsPLS package page on Github. OmicsPLS contains an implementation of O2PLS.
O2PLS is designed for integrating two high dimensional datasets and the O2PLS package is an implementation of this method.
Install the package with:
Note that copying the quotation marks can sometimes go wrong, type them yourself to be sure.
If that doesn't work, ensure that the required packages are installed (
Otherwise try the development version on this GitHub repo:
Or download the source .tar.gz or the Windows binaries .zip at my ZippedPackages repo.
After installing the package, load the functions by typing
For questions, complaints, bugs, etc, you can e-mail me (<s.el_bouhaddani at lumc.nl>) or file an issue here at GitHub.
When using the OmicsPLS R-package in your research, please cite the corresponding article by running command
or copy-paste: Bouhaddani, S., Houwing-duistermaat, J., Jongbloed, G., Salo, P., Perola, M., & Uh, H.-W. (2016). Evaluation of O2PLS in Omics data integration. BMC Bioinformatics BMTL Supplement. DOI: 10.1186/s12859-015-0854-z
Also please see http://atlasofscience.org/simultaneous-integrated-analysis-of-biological-datasets-an-evaluation-of-o2pls/ for a gentle explanation and illustration of the just mentioned article.