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Note!

This is abandoned. I don't remember the last time I used Seurat and have entirely moved to the scverse suite of tools for single-cell analysis.

ReductionWrappers

R wrappers around dimensionality reduction methods found in Python modules. Uses the reticulate package to expose functionality. Additionally provides bridging functions that let these work as drop-in replacements when working with Seurat (verions 3) and SingleCellExperiment objects. Currently wraps:

• ForceAtlas2, using the Python implementation found here. Currently works for Seurat objects only (and will remain so until I can find a fast algorithm for computing simultaneous nearest neighbors for SingleCellExperiment objects).
• openTSNE
• UMAP (Uniform Manifold Approximation and Projection)
• PaCMAP (Pairwise Controlled Manifold Approximation)
• PAGA (Partition-Based Graph Abstraction) through Scanpy.
• PHATE (Potential of Heat-diffusion for Affinity-based Trajectory Embedding)
• PhenoGraph