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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "OmicsPLS" in publications use:'
type: software
license: GPL-3.0-only
title: 'OmicsPLS: Data Integration with Two-Way Orthogonal Partial Least Squares'
version: 2.0.2
doi: 10.1186/s12859-018-2371-3
identifiers:
- type: doi
  value: 10.32614/CRAN.package.OmicsPLS
abstract: 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) <https://doi.org/10.1186/s12859-018-2371-3>, and Trygg and Wold (2003)
  <https://doi.org/10.1002/cem.775>. It also performs Sparse Group (Penalized) O2PLS,
  see Gu et al (2020) <https://doi.org/10.1186/s12859-021-03958-3> and cross-validation
  for the degree of sparsity.
authors:
- family-names: Bouhaddani
  given-names: Said el
  email: s.elbouhaddani@umcutrecht.nl
- family-names: Bouhaddani
  given-names: Said el
- family-names: Gu
  given-names: Zhujie
- family-names: Houwing-Duistermaat
  given-names: Jeanine
- family-names: Jongbloed
  given-names: Geurt
- family-names: Kielbasa
  given-names: Szymon
- family-names: Uh
  given-names: Hae-Won
preferred-citation:
  type: article
  title: Integrating omics datasets with the OmicsPLS package
  authors:
  - family-names: Bouhaddani
    given-names: el
  - name: Said
  - name: Uh
  - family-names: Won
    given-names: Hae
  - name: Jongbloed
  - name: Geurt
  - name: Hayward
  - name: Caroline
  - name: Klari'c
  - name: Lucija
  - name: Kielbasa
  - family-names: M.
    given-names: Szymon
  - name: Houwing-Duistermaat
  - name: Jeanine
  journal: BMC Bioinformatics
  year: '2018'
  volume: '19'
  issue: '1'
  abstract: 'With the exponential growth in available biomedical data, there is a
    need for data integration methods that can extract information about relationships
    between the data sets. However, these data sets might have very different characteristics.
    For interpretable results, data-specific variation needs to be quantified. For
    this task, Two-way Orthogonal Partial Least Squares (O2PLS) has been proposed.
    To facilitate application and development of the methodology, free and open-source
    software is required. However, this is not the case with O2PLS. We introduce OmicsPLS,
    an open-source implementation of the O2PLS method in R. It can handle both low-
    and high-dimensional datasets efficiently. Generic methods for inspecting and
    visualizing results are implemented. Both a standard and faster alternative cross-validation
    methods are available to determine the number of components. A simulation study
    shows good performance of OmicsPLS compared to alternatives, in terms of accuracy
    and CPU runtime. We demonstrate OmicsPLS by integrating genetic and glycomic data.
    We propose the OmicsPLS R package: a free and open-source implementation of O2PLS
    for statistical data integration. OmicsPLS is available at https://cran.r-project.org/package=OmicsPLS
    and can be installed in R via install.packages(“OmicsPLS”).'
  issn: 1471-2105
  doi: 10.1186/s12859-018-2371-3
  url: https://doi.org/10.1186/s12859-018-2371-3
repository: https://selbouhaddani-umc.r-universe.dev
commit: 688d3c067f207e4328a43f04de7957bf2d14c75c
date-released: '2021-05-19'
contact:
- family-names: Bouhaddani
  given-names: Said el
  email: s.elbouhaddani@umcutrecht.nl