embed_lsi_umap: embed lsi
In patrickCNMartin/Vesalius: Vesalius: Dissecting Tissue Anatomy from Spatial Transcriptomic Data
embed_lsi_umap R Documentation
embed lsi
Description
embed in grey scale using latent semantic indexing
followed by UMAP
Usage
embed_lsi_umap(
counts,
dimensions,
features = NULL,
remove_lsi_1,
verbose = TRUE
)
Arguments
counts
Seurat object containing normalised counts
dimensions
numeric for number of latent space dimensions to use
features
custom vector of features
remove_lsi_1
logical if first LSI dimenions should be removed
verbose
logical if progress messages should be outputed
Value
normalised LSI embedding matrix
patrickCNMartin/Vesalius documentation built on April 17, 2025, 11:31 p.m.
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| embed_lsi_umap | R Documentation |
embed lsi
Description
embed in grey scale using latent semantic indexing followed by UMAP
Usage
embed_lsi_umap(
counts,
dimensions,
features = NULL,
remove_lsi_1,
verbose = TRUE
)
Arguments
counts |
Seurat object containing normalised counts |
dimensions |
numeric for number of latent space dimensions to use |
features |
custom vector of features |
remove_lsi_1 |
logical if first LSI dimenions should be removed |
verbose |
logical if progress messages should be outputed |
Value
normalised LSI embedding matrix
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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