Transform a Seurat objects / FindAllMarkers result into a ClusterSet.

Transform a Seurat objects into a ClusterSet.

cluster_set_from_seurat(
  object = NULL,
  markers = NULL,
  layer = c("data", "counts", "scale.data"),
  assay = "RNA",
  p_val_adj = 0.001
)

Arguments

object

A Seurat object.

markers

A Seurat::FindAllMarkers() result or a named vector (clusters with gene_names as named). Named vectors can contains several position with the same gene name (overlapping clusters).

layer

One of 'data', 'counts' or 'scale.data'. The slot to extract from the seurat object to perform clustering analysis. SCT is the recommended method from Seurat package when working with spatial transcriptomics data.

assay

The type of assay (e.g. "RNA", "Spatial", "Sketch", "SCT"...).

p_val_adj

If markers is the output from Seurat::FindAllMarkers(), the adjusted p-value threshold.

Examples

## From a scRNA-seq/Seurat object
library(SeuratObject)
library(Seurat)
data("pbmc_small", package="SeuratObject")
markers <- Seurat::FindAllMarkers(pbmc_small, only.pos = TRUE)
#> Calculating cluster 0
#> Calculating cluster 1
#> Calculating cluster 2
cs <- cluster_set_from_seurat(pbmc_small, markers)
#> |-- INFO :  This seurat object contains the following assay : RNA. 
#> |-- INFO :  Computing centers. 
cs <- top_genes(cs)
#> |-- INFO :  One or several clusters contain less than 20 genes. Retrieving all genes 
#> |-- INFO :  Extracting genes with the highest mean correlation to the others... 
#> |-- INFO :  Extracting genes with the highest mean correlation to the others... 
#> |-- INFO :  Results are stored in 'top_genes' slot of the object. 
plot_heatmap(cs)
#> |-- INFO :  cell_clusters is not NULL. Setting show_dendro to FALSE 
#> |-- INFO :  Centering matrix. 
#> |-- INFO :  Ceiling matrix. 
#> |-- INFO :  Flooring matrix. 
#> |-- INFO :  Ordering cells/columns using hierarchical clustering. 
#> |-- INFO :  Plotting heatmap. 
#> |-- INFO :  Plot is interactive... 
plot_heatmap(cs)
#> |-- INFO :  cell_clusters is not NULL. Setting show_dendro to FALSE 
#> |-- INFO :  Centering matrix. 
#> |-- INFO :  Ceiling matrix. 
#> |-- INFO :  Flooring matrix. 
#> |-- INFO :  Ordering cells/columns using hierarchical clustering. 
#> |-- INFO :  Plotting heatmap. 
#> |-- INFO :  Plot is interactive... 
plot_heatmap(cs[2, ])
#> |-- INFO :  cell_clusters is not NULL. Setting show_dendro to FALSE 
#> |-- INFO :  Centering matrix. 
#> |-- INFO :  Ceiling matrix. 
#> |-- INFO :  Flooring matrix. 
#> |-- INFO :  Ordering cells/columns using hierarchical clustering. 
#> |-- INFO :  Some columns have sd equal to 0. Can not compute HC... 
#> Error: |-- STOP : Use cell_clusters argument for ordering..
plot_heatmap(cs, cell_clusters = Seurat::Idents(pbmc_small))
#> |-- INFO :  Extracting cell identity. 
#> |-- INFO :  Centering matrix. 
#> |-- INFO :  Ceiling matrix. 
#> |-- INFO :  Flooring matrix. 
#> |-- INFO :  Plotting heatmap. 
#> |-- INFO :  Plot is interactive... 
plot_heatmap(cs[1,Idents(pbmc_small) == "0"], 
cell_clusters = Seurat::Idents(pbmc_small), label_size = 6)
#> |-- INFO :  Extracting cell identity. 
#> |-- INFO :  Centering matrix. 
#> |-- INFO :  Ceiling matrix. 
#> |-- INFO :  Flooring matrix. 
#> |-- INFO :  Plotting heatmap. 
#> |-- INFO :  Plot is interactive... 
plot_profiles(cs, ident = Seurat::Idents(pbmc_small))
#> |-- INFO :  Number of cells types: 3 
#> |-- INFO :  Number of cells: 80