This case study introduces multiblock sparse PLS (Block sPLS) using a single-cell multi-omics dataset from mouse gastrulation. Block sPLS integrates multiple datasets measured on the same samples—in this case, RNA expression, DNA methylation, and chromatin accessibility—to uncover shared patterns across modalities. You’ll explore pairwise relationships, build a multiblock model, and interpret complex molecular variation using plots like sample projections, arrows, and circos networks.
🔍 More on Multiblock sPLS
🔍 More on design matrix for multiblock methods
📄 Download R script
📦 Download dataset
Data used on this page:
Single cell gastrulation data (not in mixOmics package)
Key functions used on this page:pls()block.spls()plotIndiv()plotArrow()plotVar()circosPlot()
References:
1. Argelaguet, R., Clark, S.J., Mohammed, H. et al. Multi-omics profiling of mouse gastrulation at single-cell resolution. Nature 576, 487–491 (2019). https://doi.org/10.1038/s41586-019-1825-8