text: import anndata
  import os
  import numpy as np
  import scipy.sparse
  
  from sfaira.data import DatasetBase
  
  SAMPLE_FNS = [
      "wang20_colon.processed.h5ad",
      "wang20_ileum.processed.h5ad",
      "wang20_rectum.processed.h5ad"
  ]
  
  
  class Dataset(DatasetBase):
  
      def __init__(self, **kwargs):
          super().__init__(**kwargs)
          self.download_url_data = f"https://covid19.cog.sanger.ac.uk/{self.sample_fn}"
          self.download_url_meta = None
  
          organ = self.sample_fn.split("_")[1].split(".")[0]
  
          self.assay_sc = "10x 3' transcription profiling"
          self.author = "Wang"
          self.disease = "healthy"
          self.doi_journal = "10.1084/jem.20191130"
          self.layer_counts = "X"
          self.organ = organ
          self.organism = "Homo sapiens"
          self.primary_data = True
          self.sample_source = "primary_tissue"
          self.year = 2019
  
          self.feature_symbol_var_key = "index"
          self.feature_type = "rna"
          self.cell_type_obs_key = "CellType"
  
          self.set_dataset_id(idx=1)
  
  
  def load(data_dir, sample_fn, **kwargs):
      fn = os.path.join(data_dir, sample_fn)
      adata = anndata.read(fn)
      adata.X = np.expm1(adata.X)
      adata.X = adata.X.multiply(scipy.sparse.csc_matrix(adata.obs["n_counts"].values[:, None])).multiply(1 / 10000)
  
      return adata
  