AnnData-Conversion {zellkonverter} | R Documentation |
Conversion between Python AnnData objects and SingleCellExperiment objects.
AnnData2SCE( adata, X_name = NULL, layers = TRUE, uns = TRUE, var = TRUE, obs = TRUE, varm = TRUE, obsm = TRUE, varp = TRUE, obsp = TRUE, raw = FALSE, skip_assays = FALSE, hdf5_backed = TRUE, verbose = NULL ) SCE2AnnData( sce, X_name = NULL, assays = TRUE, colData = TRUE, rowData = TRUE, varm = TRUE, reducedDims = TRUE, metadata = TRUE, colPairs = TRUE, rowPairs = TRUE, skip_assays = FALSE, verbose = NULL )
adata |
A reticulate reference to a Python AnnData object. |
X_name |
For |
layers, uns, var, obs, varm, obsm, varp, obsp, raw |
Arguments specifying how
these slots are converted. If |
skip_assays |
Logical scalar indicating whether to skip conversion of
any assays in |
hdf5_backed |
Logical scalar indicating whether HDF5-backed matrices
in |
verbose |
Logical scalar indicating whether to print progress messages.
If |
sce |
A SingleCellExperiment object. |
assays, colData, rowData, reducedDims, metadata, colPairs, rowPairs |
Arguments specifying how these slots are converted. If |
These functions assume that an appropriate Python environment has already been loaded. As such, they are largely intended for developer use, most typically inside a basilisk context.
The conversion is not entirely lossless. The current mapping is shown below (also at https://tinyurl.com/AnnData2SCE):
In SCE2AnnData()
, matrices are converted to a numpy-friendly format.
Sparse matrices are converted to dgCMatrix objects while all
other matrices are converted into ordinary matrices. If skip_assays = TRUE
,
empty sparse matrices are created instead and the user is expected to fill in
the assays on the Python side.
For AnnData2SCE()
, a warning is raised if there is no corresponding R
format for a matrix in the AnnData object, and an empty sparse matrix is
created instead as a placeholder. If skip_assays = NA
, no warning is
emitted but variables are created in the int_metadata()
of the output to
specify which assays were skipped.
If skip_assays = TRUE
, empty sparse matrices are created for all assays,
regardless of whether they might be convertible to an R format or not.
In both cases, the user is expected to fill in the assays on the R side,
see readH5AD()
for an example.
We attempt to convert between items in the SingleCellExperiment
metadata()
slot and the AnnData
uns
slot. If an item cannot be
converted a warning will be raised.
Values stored in the varm
slot of an AnnData
object are stored in a
column of rowData()
in a SingleCellExperiment
as a DataFrame of matrices. If this column is present an
attempt is made to transfer this information when converting from
SingleCellExperiment to AnnData
.
AnnData2SCE()
will return a SingleCellExperiment
containing the equivalent data from adata
.
SCE2AnnData()
will return a reticulate reference to an AnnData object
containing the content of sce
.
Luke Zappia
Aaron Lun
writeH5AD()
and readH5AD()
for dealing directly with H5AD files.
if (requireNamespace("scRNAseq", quietly = TRUE)) { library(basilisk) library(scRNAseq) seger <- SegerstolpePancreasData() # These functions are designed to be run inside # a specified Python environment roundtrip <- basiliskRun(fun = function(sce) { # Convert SCE to AnnData: adata <- zellkonverter::SCE2AnnData(sce) # Maybe do some work in Python on 'adata': # BLAH BLAH BLAH # Convert back to an SCE: zellkonverter::AnnData2SCE(adata) }, env = zellkonverterAnnDataEnv, sce = seger) }