Merge 10x Visium data

Merges two or more Seurat objects containing SRT data while making sure that the spatial data (images and spot coordinates) are handled correctly.

Usage

MergeSTData(
  x,
  y,
  merge_data = TRUE,
  merge_dr = NULL,
  project = "SeuratProject"
)

Arguments

x

A Seurat object

y

A Seurat object or a list of Seurat objects

merge_data

Merge the data slots instead of just merging the counts (which requires re-normalization); this is recommended if the same normalization approach was applied to all objects. See merge for details.

merge_dr

Merge specified DimReducs that are present in all objects; will only merge the embeddings slots for the first N dimensions that are shared across all objects. See merge for details.

project

Project name for the Seurat object

Value

A merged Seurat object

Details

NB: If you use the generic merge function you will not be able to use any of the semla visualization methods on the output object as the Staffli object will be broken.

See also

Other subset-and-merge: SubsetSTData()

Author

Ludvig Larsson

Examples

se_mbrain <- readRDS(system.file("extdata",
                                 "mousebrain/se_mbrain",
                                 package = "semla"))
se_mcolon <- readRDS(system.file("extdata",
                                 "mousecolon/se_mcolon",
                                 package = "semla"))

se_mbrain
#> An object of class Seurat 
#> 188 features across 2560 samples within 1 assay 
#> Active assay: Spatial (188 features, 170 variable features)
#>  2 layers present: counts, data
se_mcolon
#> An object of class Seurat 
#> 188 features across 2604 samples within 1 assay 
#> Active assay: Spatial (188 features, 182 variable features)
#>  2 layers present: counts, data

# Merge a mousebrain dataset with two mousecolon datasets
se_merged <- MergeSTData(x = se_mbrain, y = se_mcolon)
se_merged
#> An object of class Seurat 
#> 188 features across 5164 samples within 1 assay 
#> Active assay: Spatial (188 features, 0 variable features)
#>  2 layers present: counts, data

# Plot H&E images
ImagePlot(se_merged |> LoadImages(verbose = FALSE))