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) <doi:10.1186/s12859-018-2371-3>, and Trygg and Wold (2003) <doi:10.1002/cem.775>. It also performs Sparse Group (Penalized) O2PLS, see Gu et al (2020) <doi:10.1186/s12859-021-03958-3> and cross-validation for the degree of sparsity.
|Author||Said el Bouhaddani, Zhujie Gu, Jeanine Houwing-Duistermaat, Geurt Jongbloed, Szymon Kielbasa and Hae-Won Uh|
|Maintainer||Said el Bouhaddani <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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