Converts a Python AnnData h5ad file to a Seurat rds file, preserving spatial coordinates, dimensional reductions, and optionally SCT-transformed data.
Usage
h5ad2rds(
file_path = NULL,
data_type = "stRNA",
convert_mode = "scanpy",
assay_id = NULL,
X_index = "rawX",
binsize = 1,
SCT_index = FALSE,
reduction_index = FALSE,
image_index = NULL,
return_object = TRUE,
grp_nm = NULL,
dir_nm = "M0_h5ad2rds"
)Arguments
- file_path
Character, path to the input h5ad file
- data_type
Character, data type - "stRNA" (spatial) or "scRNA" (single-cell) (default: "stRNA")
- convert_mode
Character, conversion method - "scanpy" or "seurat" (default: "scanpy")
- assay_id
Character, assay name for the Seurat object (default: NULL, auto-detected based on data_type)
- X_index
Character, which matrix to use as counts - "X" or "rawX" (default: "rawX")
- binsize
Numeric, bin size for spatial coordinate scaling (default: 1)
- SCT_index
Logical, whether to convert SCT results from stereopy (default: FALSE)
- reduction_index
Logical, whether to preserve dimensional reductions (default: FALSE)
- image_index
Logical, whether to create spatial image object (default: NULL, auto-detected based on data_type)
- return_object
Logical, whether to return the Seurat object (default: TRUE)
- grp_nm
Character, group name for output organization (default: "sample1")
- dir_nm
Character, directory name for output (default: "M0_h5ad2rds")
Examples
if (FALSE) { # \dontrun{
# Convert spatial transcriptomics h5ad to Seurat
configure_conda()
seurat_obj <- h5ad2rds(
file_path = "data/spatial_data.h5ad",
data_type = "stRNA",
binsize = 100,
reduction_index = TRUE,
image_index = TRUE
)
} # }