code: def krumsiek11() -> AnnData:
      
      filename = os.path.dirname(__file__) + '/krumsiek11.txt'
      verbosity_save = sc.settings.verbosity
      sc.settings.verbosity = 'error'  # suppress output...
      adata = sc.read(filename, first_column_names=True)
      sc.settings.verbosity = verbosity_save
      adata.uns['iroot'] = 0
      fate_labels = {0: 'Stem', 159: 'Mo', 319: 'Ery',
                     459: 'Mk', 619: 'Neu'}
      adata.uns['highlights'] = fate_labels
      cell_type = np.array(['progenitor' for i in range(adata.n_obs)])
      cell_type[80:160] = 'Mo'
      cell_type[240:320] = 'Ery'
      cell_type[400:480] = 'Mk'
      cell_type[560:640] = 'Neu'
      adata.obs['cell_type'] = cell_type
      sc.utils.sanitize_anndata(adata)
      return adata
docs: Simulated myeloid progenitors [Krumsiek11]_.
  
      The literature-curated boolean network from [Krumsiek11]_ was used to
      simulate the data. It describes development to four cell fates: 'monocyte',
      'erythrocyte', 'megakaryocyte' and 'neutrophil'.
  
      See also the discussion of this data in [Wolf19]_.
  
      Simulate via :func:`~scanpy.api.sim`.
  
      Returns
      -------
      Annotated data matrix.