c(
person("Terrence", "Ernst", role = c("aut"),
comment = "Web application"),
person("John", "Blischak", role = c("aut", "cre"),
email = "jdblischak@gmail.com",
comment = c(ORCID = "0000-0003-2634-9879")),
person("Paul", "Nordlund", role = c("aut"),
comment = "Web application"),
person("Justin", "Moore", role = c("aut"),
comment = "UpSet-related functions and web application"),
person("Joe", "Dalen", role = c("aut"),
comment = "Barcode functionality and web application"),
person("Akshay", "Bhamidipati", role = c("aut"),
comment = "Web application"),
person("Brett", "Engelmann", role = c("aut"),
email = "brett.engelmann@abbvie.com"),
person("Marco", "Curado", role = c("aut"),
comment = "Improved plotting capabilities"),
person(given = "AbbVie Inc.", role = c("cph", "fnd"))
)
Terrence Ernst [aut] (Web application),
John Blischak [aut, cre] (<https://orcid.org/0000-0003-2634-9879>),
Paul Nordlund [aut] (Web application),
Justin Moore [aut] (UpSet-related functions and web application),
Joe Dalen [aut] (Barcode functionality and web application),
Akshay Bhamidipati [aut] (Web application),
Brett Engelmann [aut],
Marco Curado [aut] (Improved plotting capabilities),
AbbVie Inc. [cph, fnd]

Perform Two-Way Orthogonal Partial Least Squares
Said el Bouhaddani, Jeanine Houwing-Duistermaat, Geurt Jongbloed, Szymon Kielbasa and
Hae-Won Uh
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 your results.
See Trygg and Wold (2003) <doi:10.1002/cem.775> and el Bouhaddani et al (2016) <doi:10.1186/s12859-015-0854-z>.

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 Trygg and Wold (2003) <doi:10.1002/cem.775> and el Bouhaddani et al (2016) <doi:10.1186/s12859-015-0854-z>.