coembedding_umap: Calculate UMAP projections for coembedding of cells and...

In ProFAST: Probabilistic Factor Analysis for Spatially-Aware Dimension Reduction

Calculate UMAP projections for coembedding of cells and features

Description

Calculate UMAP projections for coembedding of cells and features

Usage

coembedding_umap(
  seu,
  reduction,
  reduction.name,
  gene.set = NULL,
  slot = "data",
  assay = "RNA",
  seed = 1
)

Arguments

seu	a Seurat object with coembedding in the reductions slot wiht component name reduction.
reduction	a string, specify the reduction component that denotes coembedding.
reduction.name	a string, specify the reduction name for the obtained UMAP projection.
gene.set	a string vector, specify the features (genes) in calculating the UMAP projection, default as all features.
slot	an optional string, specify the slot in the assay, default as 'data'.
assay	an optional string, specify the assay name in the Seurat object when adding the UMAP projection.
seed	an optional integer, specify the random seed for reproducibility.

Details

None

Value

return a revised Seurat object by adding a new reduction component named 'reduction.name'.

References

None

See Also

None

Examples

data(pbmc3k_subset)
data(top5_signatures)

pbmc3k_subset <- coembedding_umap(
  pbmc3k_subset, reduction = "ncfm", reduction.name = "UMAPsig",
  gene.set = top5_signatures$gene
)

ProFAST documentation built on May 29, 2024, 7:15 a.m.