Convert an AnnData object (or a .h5ad file) to a Seurat object — convert_anndata_to

Reverse direction of `convert_to_anndata()`: takes an AnnData object (typically loaded with `anndata::read_h5ad()`) or a path to an `.h5ad` file and constructs a Seurat object. Counts go into the `counts` layer, `adata$X` into the `data` layer, `adata$obs` into the meta.data, and entries of `adata$obsm` are attached as `DimReduc` objects.

Usage

convert_anndata_to_seurat(
  adata,
  counts_layer = c("counts", "raw_counts", "raw_count"),
  assay = "RNA",
  reduction_map = list(),
  conda_env = NULL,
  orig.ident = NULL,
  use_raw = c("auto", "always", "never"),
  attach_obsp = TRUE
)

Arguments

adata: An AnnData object, OR a character path to an `.h5ad` file (in which case it is read with `anndata::read_h5ad()`).
counts_layer: Name(s) of the layer in `adata$layers` to use as the counts matrix. May be a single string or a character vector of candidate names; the first one present in `adata$layers` is used. If none are present, `adata$X` is used as counts and no separate `data` layer is added. Defaults to `c("counts", "raw_counts", "raw_count")`.
assay: Name of the resulting Seurat assay. Defaults to `"RNA"`.
reduction_map: Optional named list passed to `attach_reductions_seurat()` to override or extend the default obsm-key to Seurat-reduction mapping. See `default_reduction_map()`.
conda_env: Optional conda environment to activate before reading the file. Equivalent to calling `setup_anndata_python(conda_env)` first. Only relevant when `adata` is a path.
orig.ident: Optional value for the `orig.ident` column of the resulting Seurat meta.data. If `NULL` (default), the value is taken from `adata$uns$conversion_source` if present, otherwise from the file basename when `adata` was passed as a path, otherwise `"AnnData"`.
use_raw: How to handle `adata$raw` (a separate AnnData snapshot often used by scanpy to retain raw counts after normalising `X`). `"auto"` (default) uses `raw$X` as the counts layer when no `counts_layer` candidate matched and `adata$raw` is set; `TRUE` always uses `raw$X` as counts (and falls back to candidates / `X` if it is missing); `FALSE` ignores raw entirely.
attach_obsp: Logical. When `TRUE` (default), entries of `adata$obsp` (cell x cell pairwise matrices, e.g. nearest-neighbor graphs from `sc.pp.neighbors`) are attached as Seurat `Graphs`.

Value

A Seurat object.

Details

The returned object has the AnnData orientation transposed: Seurat stores genes x cells while AnnData stores cells x genes. Cell and feature names are taken from `adata$obs_names` and `adata$var_names`.

`adata$obs` is attached as `meta.data`. `adata$var` is attached via `seurat_obj[["RNA"]][[]] <- ...` when present and dimensionally compatible.

Examples

if (FALSE) { # \dontrun{
# Path entrypoint:
seurat_obj <- convert_anndata_to_seurat("pbmc.h5ad")

# Object entrypoint:
adata <- anndata::read_h5ad("pbmc.h5ad")
seurat_obj <- convert_anndata_to_seurat(adata)

# Custom layer + extra reductions:
seurat_obj <- convert_anndata_to_seurat(
  "pbmc.h5ad",
  counts_layer = c("counts", "raw_counts"),
  reduction_map = list(X_my_emb = list(name = "myemb", key = "MyEmb_"))
)
} # }