AddUMAP

Run UMAP dimensionality reduction on selected features.

An efficient data integration method is provided for multiple spatial transcriptomics data with non-cluster-relevant effects such as the complex batch effects. It unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, requiring only partially shared cell/domain clusters across datasets. More details can be referred to Wei Liu, et al. (2023) <doi:10.1038/s41467-023-35947-w>.

Wei Liu

PRECAST

Embedding and Clustering with Alignment for Spatial Datasets

Yi Yang

Jin Liu

AddUMAP function

<dl> <dt>seuInt</dt>
<dd>a Seurat object.</dd> <dt>n_comp</dt>
<dd>an optional positive integer, specify the number of features to be extracted.</dd> <dt>reduction</dt>
<dd>an optional string, means which dimensional reduction (e.g. PRECAST, PCA) to use for the UMAP. Default is PRECAST.</dd> <dt>assay</dt>
<dd>Name of assay that that t-SNE is being run on.</dd> <dt>seed</dt>
<dd>an optional integer, the random seed to evaluate UMAP.</dd></dl>

Arguments

Author

Add UMAP embeddings for a Seurat object — AddUMAP

<dl>

 <dt>seuInt</dt>
<dd>a Seurat object.</dd>

 <dt>n_comp</dt>
<dd>an optional positive integer, specify the number of features to be extracted.</dd>

 <dt>reduction</dt>
<dd>an optional string, means which dimensional reduction (e.g. PRECAST, PCA) to use for the UMAP. Default is PRECAST.</dd>

 <dt>assay</dt>
<dd>Name of assay that that t-SNE is being run on.</dd>

 <dt>seed</dt>
<dd>an optional integer, the random seed to evaluate UMAP.</dd>

</dl>

AddUMAP: Add UMAP embeddings for a Seurat object

Description

Usage

Value

Arguments

Author

Details

See Also