Convert a Seurat V4 object to a Giotto object

Usage

seuratToGiottoV4(
  sobject,
  spatial_assay = "Spatial",
  dim_reduction = c("pca", "umap"),
  subcellular_assay = "Vizgen",
  sp_network = NULL,
  nn_network = NULL,
  verbose = TRUE
)

Arguments

sobject: Input Seurat object to convert to Giotto object
spatial_assay: Specify name of the spatial assay slot in Seurat. Default is "Spatial".
dim_reduction: Specify which dimensional reduction computations to fetch from input Seurat object. Default is "c('pca', 'umap')".
subcellular_assay: Specify name of the subcellular assay in input
sp_network: sp_network
nn_network: nn_network
verbose: logical. Default to TRUE object. Default is "Vizgen".

Value

A Giotto object converted from Seurat object with all computations stored in it.

Examples

m_expression <- Matrix::Matrix(rnorm(100), nrow = 10, sparse = TRUE)
s <- Seurat::CreateSeuratObject(counts = m_expression)

seuratToGiottoV5(s, spatial_assay = "RNA")
#> Warning: data layer is not found and counts layer is used
#> Images for RNA assay not found in the data.
#>                         Skipping image processing.
#> python already initialized in this session
#>  active environment : 'giotto_env'
#>  python version : 3.10
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#>  "/usr/share/miniconda/envs/giotto_env/bin/python"
#> There are non numeric or integer columns for the spatial location
#>  input at column position(s): 1
#>  The first non-numeric column will be considered as a cell ID
#>  to test for consistency with the expression matrix
#>  Other non numeric columns will be removed
#> An object of class giotto 
#> >Active spat_unit:  cell 
#> >Active feat_type:  rna 
#> dimensions    : 10, 10 (features, cells)
#> [SUBCELLULAR INFO]
#> [AGGREGATE INFO]
#> expression -----------------------
#>   [cell][rna] raw normalized
#> spatial locations ----------------
#>   [cell] raw
#> 
#> 
#> Use objHistory() to see steps and params used