CAESAR.coembedding: Compute Co-embedding Using CAESAR

In CAESAR.Suite: CAESAR: a Cross-Technology and Cross-Resolution Framework for Spatial Omics Annotation

Compute Co-embedding Using CAESAR

Description

This function performs co-embedding of both cells and genes using the CAESAR method. It integrates spatial transcriptomics data from a Seurat object ('seu') with a spatial adjacency matrix to compute the low-dimensional co-embedding.

Usage

CAESAR.coembedding(
  seu,
  pos,
  reduction.name = "caesar",
  q = 50,
  radius.upper = 400,
  ...
)

Arguments

seu	A Seurat object containing spatial transcriptomics data.
pos	A matrix of spatial coordinates for the spots (e.g., spatial positions of cells or pixels in the image). The row names of 'pos' should match the column names of 'seu'.
reduction.name	A character string specifying the name of the dimensional reduction method to store in the Seurat object. Default is "caesar".
q	An integer specifying the number of dimensions for the reduced co-embeddings. Default is 50.
radius.upper	A numeric value specifying the upper limit of the search radius for the spatial adjacency matrix. Default is 400.
...	Additional arguments passed to 'cellembedding_image_seurat'.

Value

The modified Seurat object with the computed cell and gene embeddings stored in the specified reduction slot.

See Also

cellembedding_seurat for computing cell embeddings. add.gene.embedding for adding gene embeddings to a Seurat object.

Examples

data(toydata)

seu <- toydata$seu
pos <- toydata$pos

seu <- CAESAR.coembedding(
    seu = seu,
    pos = pos
)
print(seu)

CAESAR.Suite documentation built on April 3, 2025, 10:32 p.m.