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Class for Anndata

AnnDataParser.Rd

This class helps dealing with h5ad objects from Python AnnData. You have several options will allow for retrieval of the underlying data.

Methods

Public methods

AnnDataParser$new()

Initialises the Anndata Parser.

Usage

AnnDataParser$new(h5_path)

Arguments

h5_path

String. Path to the h5 file.

Returns

Returns the initialised class.

AnnDataParser$get_obs_table()

Returns the observation table with all the data from the h5ad file.

Usage

AnnDataParser$get_obs_table()

Returns

data.table. The found observations are returned. The pandas index will be named sample_id. Remaining columns (if found) will be returned as factors due to the way the data is stored in h5.

AnnDataParser$get_var_info()

Returns the variable table with all the data from the h5ad file.

Usage

AnnDataParser$get_var_info()

Returns

data.table. The found observations are returned. The pandas index will be named var_id. Remaining columns (if found) will be returned as factors due to the way the data is stored in h5.

AnnDataParser$get_raw_counts()

Returns the counts that are stored in X slot of the anndata object.

Usage

AnnDataParser$get_raw_counts()

Returns

Returns the count matrix with samples = columns and rows = features.

AnnDataParser$get_key_data()

Wrapper function that returns a list of the stored count data and the metadata found in the h5ad file.

Usage

AnnDataParser$get_key_data()

Returns

List with following elements:

  • metadata - metadata from the respective h5ad file

  • var_info - metadata on the variables from the respective h5ad file.

  • counts - counts that were found in the h5ad file.

AnnDataParser$clone()

The objects of this class are cloneable with this method.

Usage

AnnDataParser$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# parse counts and obs back out of a small h5ad file
set.seed(42)
counts <- matrix(rpois(50, 5), nrow = 10, ncol = 5)
obs <- data.table::data.table(sample_id = sprintf("cell_%i", 1:10))
var <- data.table::data.table(var_id = sprintf("gene_%i", 1:5))
h5_path <- tempfile(fileext = ".h5ad")
write_h5ad_sc_dense(h5_path, counts, obs, var, .verbose = FALSE)
parser <- AnnDataParser$new(h5_path)
dim(parser$get_raw_counts())
#> [1]  5 10
head(parser$get_obs_table())
#>    sample_id
#>       <char>
#> 1:    cell_1
#> 2:    cell_2
#> 3:    cell_3
#> 4:    cell_4
#> 5:    cell_5
#> 6:    cell_6
unlink(h5_path)