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ConsensusOPLS

1.1.0

Consensus OPLS for Multi-Block Data Fusion

1packages depend
2.4Kdownloads / year
77.0%test coverage
13/13checks pass

Overview

About
Maintained by Van Du T. TranFirst published 2024-06-202 releasesCRAN page ↗

Merging data from multiple sources is a relevant approach for comprehensively evaluating complex systems. However, the inherent problems encountered when analyzing single tables are amplified with the generation of multi-block datasets, and finding the relationships between data layers of increasing complexity constitutes a challenging task. For that purpose, a generic methodology is proposed by combining the strength of established data analysis strategies, i.e. multi-block approaches and the Orthogonal Partial Least Squares (OPLS) framework to provide an efficient tool for the fusion of data obtained from multiple sources. The package enables quick and efficient implementation of the consensus OPLS model for any horizontal multi-block data structures (observation-based matching). Moreover, it offers an interesting range of metrics and graphics to help to determine the optimal number of components and check the validity of the model through permutation tests. Interpretation tools include score and loading plots, Variable Importance in Projection (VIP), functionality predict for SHAP computing, and performance coefficients such as R2, Q2, and DQ2 coefficients. J. Boccard and D.N. Rutledge (2013) doi:10.1016/j.aca.2013.01.022.

Install

Health

CRAN checks
13OK
Slowest check: 9.9 min · r-devel-windows-x86_64
Code health
Yes
Tests · ratio 0.10
77.0%
Coverage · measured lines
100%
Documentation · exports
7
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-04-25
    12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-03-10
    11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
98%
Return-value docs
89%
References docs
8%

Downloads

2.4K
CRAN downloads in the past year
Rank #15,550 · ~7/day · ~204/mo
Daily download trend is not available in this view yet.
19830 days
69090 days
2.4K1 year
Compare downloads with other packages →
Also on207 r2u28 autocran

Dependencies

Declared dependencies
9 external dependencies (excludes base and recommended)
Depends (6)
R >= 4.0.0statsutilsgraphicsgrDevicesmethods
Imports (2)
parallelreshape2
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
1direct
0indirect

Code & Tests

Datasets

People & History

People (6)
Maintainer (1)
Author, Maintainer
Authors (4)
Author, Maintainer
Funders (2)
Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • 1.1.0Latest
    2025-02-27 · current release · diff ↗
  • 1.0.0
    2024-06-20
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2024-06-20
Total releases
2 / 2 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.0.0
Bundled data
32 KB / 1 file
Download size
3.4 MB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ConsensusOPLS")
Tran, V. D. T., Boccard, J., Bougel, C., Ibberson, M., Mehl, F., & Tremblay-Franco, M. (2025). ConsensusOPLS: Consensus OPLS for Multi-Block Data Fusion (Version 1.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.ConsensusOPLS

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for ConsensusOPLS version 1.1.0 [Data set]. HJJB, LLC. Data release v2026-08-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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