We provide R implementation of DIVAS (Prothero et al., 2024),a statistical method for multi-modal data integration. Via statistical analysis of subspaces, DIVAS identifies joint, partially shared and individual variations of multiple data blocks in a completely data driven way. In addition to providing an R implementation based on the original MATLAB implementation, we also designed visualisation tools for exploring DIVAS results.
The DIVAS package requires the CVXR package to be able to use optimisation solvers like SCS.
We strongly recommend installing the latest stable version from CRAN.
# Install devtools (if not already installed)
install.packages("devtools")
# Install the latest version of CVXR from CRAN
# This is critical to avoid issues with solver status recognition (e.g., for SCS)
install.packages("CVXR")You can install the development version of DIVAS from GitHub using devtools:
# Install DIVAS package from the main branch on GitHub
devtools::install_github("ByronSyun/DIVAS_Develop/pkg", ref = "main")
# Or install from a local folder if you have cloned the repository
# devtools::install("path/to/DIVAS-main/pkg")We provide the following examples to illustrate the use of DIVAS in different scenarios.
| Dataset | Brief Description | Vignette Link | Format | Primary Reference |
|---|---|---|---|---|
| toyDataThreeWay.mat | Synthetic 3-block data with known joint structures | Toy Dataset Example | .mat | Prothero et al. (2024) |
| gnp_imputed.qs | GNP economic time series data | GNP Dataset Example | .qs | Stock & Watson (2016) |
| COVID-19 Multi-Omics | 6-block integration: scRNA-seq (4 cell types), proteomics, metabolomics from 114 COVID-19 patient samples | COVID Case Study | .rds | Su et al. (2020) |
- Jiadong Mao - Lead Developer, Maintainer
- Yinuo Sun - Package Developer, Maintainer
Prothero, J., et al. (2024). Data integration via analysis of subspaces (DIVAS). TEST.
This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3) - see the LICENSE file for details.