From f1c40faefbda3d62c6e7aa9f1baafade82cc24ab Mon Sep 17 00:00:00 2001
From: felixpetschko <felixpetschko@gmail.com>
Date: Tue, 17 Sep 2024 18:38:28 +0200
Subject: [PATCH 1/5] convert cell_indices str->array dict to a csr matrix
 before storing the anndata result

---
 src/scirpy/tl/_clonotypes.py | 20 +++++++++++++++++++-
 1 file changed, 19 insertions(+), 1 deletion(-)

diff --git a/src/scirpy/tl/_clonotypes.py b/src/scirpy/tl/_clonotypes.py
index 59e5cc94f..1116102c6 100644
--- a/src/scirpy/tl/_clonotypes.py
+++ b/src/scirpy/tl/_clonotypes.py
@@ -332,10 +332,28 @@ def define_clonotype_clusters(
     clonotype_cluster_series = pd.Series(values, index=idx).reindex(params.adata.obs_names)
     clonotype_cluster_size_series = clonotype_cluster_series.groupby(clonotype_cluster_series).transform("count")
 
+    def convert_str_array_dict_to_csr(str_array_dict: dict[str, np.ndarray[str]]) -> sp.csr_matrix:
+        num_rows = len(str_array_dict)
+
+        data_arrays = [np.array([])] * num_rows
+        indices_arrays = [np.array([])] * num_rows
+        nnz_array = np.zeros(num_rows)
+
+        for key_str, value in str_array_dict.items():
+            key = int(key_str)
+            data_arrays[key] = value.astype(int)
+            indices_arrays[key] = np.array(range(0,len(value)))
+            nnz_array[key] = len(value)
+
+        data = np.concatenate(data_arrays)
+        indices = np.concatenate(indices_arrays)
+        indptr = np.concatenate([np.array([0]), np.cumsum(nnz_array)])
+        return sp.csr_matrix((data, indices, indptr))
+
     # Return or store results
     clonotype_distance_res = {
         "distances": clonotype_dist,
-        "cell_indices": ctn.cell_indices,
+        "cell_indices": convert_str_array_dict_to_csr(ctn.cell_indices),
     }
     if inplace:
         params.set_obs(key_added, clonotype_cluster_series)

From 97e13b75b27398fdbace516403c37091424f02ab Mon Sep 17 00:00:00 2001
From: felixpetschko <felixpetschko@gmail.com>
Date: Wed, 18 Sep 2024 19:09:38 +0200
Subject: [PATCH 2/5] save cell_indices as json format

---
 src/scirpy/ir_dist/_clonotype_neighbors.py |  2 +-
 src/scirpy/pl/_clonotypes.py               |  4 +++-
 src/scirpy/tests/test_ir_query.py          | 10 ++++++++--
 src/scirpy/tl/_clonotypes.py               | 15 +++++++++------
 src/scirpy/tl/_ir_query.py                 | 18 +++++++++++-------
 src/scirpy/util/__init__.py                | 18 ++++++++++++++++++
 6 files changed, 50 insertions(+), 17 deletions(-)

diff --git a/src/scirpy/ir_dist/_clonotype_neighbors.py b/src/scirpy/ir_dist/_clonotype_neighbors.py
index c948c617e..e615734da 100644
--- a/src/scirpy/ir_dist/_clonotype_neighbors.py
+++ b/src/scirpy/ir_dist/_clonotype_neighbors.py
@@ -118,7 +118,7 @@ def _make_clonotype_table(self, params: DataHandler) -> tuple[Mapping, pd.DataFr
                     ct_tuple[0] if len(ct_tuple) == 1 else ct_tuple,
                     [],
                 )
-            ].values
+            ].values.tolist()
             for i, ct_tuple in enumerate(clonotypes.itertuples(index=False, name=None))
         }
 
diff --git a/src/scirpy/pl/_clonotypes.py b/src/scirpy/pl/_clonotypes.py
index da493921c..e6cb28ab0 100644
--- a/src/scirpy/pl/_clonotypes.py
+++ b/src/scirpy/pl/_clonotypes.py
@@ -22,7 +22,7 @@
 from scipy.sparse import issparse
 
 from scirpy.tl._clonotypes import _doc_clonotype_network, _graph_from_coordinates
-from scirpy.util import DataHandler
+from scirpy.util import DataHandler, read_cell_indices
 from scirpy.util.graph import _distance_to_connectivity
 
 from .styling import _get_colors, _init_ax
@@ -413,6 +413,8 @@ def _plot_clonotype_network_panel(
     scale_by_n_cells,
     color_by_n_cells,
 ):
+    cell_indices = read_cell_indices(cell_indices)
+    
     colorbar_title = "mean per dot"
     pie_colors = None
     cat_colors = None
diff --git a/src/scirpy/tests/test_ir_query.py b/src/scirpy/tests/test_ir_query.py
index 2713f2718..dfc10150e 100644
--- a/src/scirpy/tests/test_ir_query.py
+++ b/src/scirpy/tests/test_ir_query.py
@@ -5,6 +5,8 @@
 import pytest
 from mudata import MuData
 
+from scirpy.util import read_cell_indices
+
 from scirpy.pp import ir_dist
 from scirpy.tl._ir_query import (
     _reduce_json,
@@ -32,9 +34,13 @@ def test_ir_query(adata_cdr3, adata_cdr3_2, metric, key1, key2):
 
     tmp_key2 = f"ir_query_TESTDB_aa_{metric}" if key2 is None else key2
     tmp_ad = adata_cdr3.mod["airr"] if isinstance(adata_cdr3, MuData) else adata_cdr3
+    
+    cell_indices = read_cell_indices(tmp_ad.uns[tmp_key2]["cell_indices"])
+    cell_indices_reference = read_cell_indices(tmp_ad.uns[tmp_key2]["cell_indices_reference"])
+    
     assert tmp_ad.uns[tmp_key2]["distances"].shape == (4, 3)
-    assert len(tmp_ad.uns[tmp_key2]["cell_indices"]) == 4
-    assert len(tmp_ad.uns[tmp_key2]["cell_indices_reference"]) == 3
+    assert len(cell_indices) == 4
+    assert len(cell_indices_reference) == 3
 
 
 @pytest.mark.parametrize(
diff --git a/src/scirpy/tl/_clonotypes.py b/src/scirpy/tl/_clonotypes.py
index 1116102c6..0a0aafa19 100644
--- a/src/scirpy/tl/_clonotypes.py
+++ b/src/scirpy/tl/_clonotypes.py
@@ -9,11 +9,12 @@
 import scipy.sparse as sp
 from anndata import AnnData
 from scanpy import logging
+import json
 
 from scirpy.ir_dist import MetricType, _get_metric_key
 from scirpy.ir_dist._clonotype_neighbors import ClonotypeNeighbors
 from scirpy.pp import ir_dist
-from scirpy.util import DataHandler
+from scirpy.util import DataHandler, read_cell_indices
 from scirpy.util.graph import igraph_from_sparse_matrix, layout_components
 
 _common_doc = """\
@@ -89,7 +90,7 @@
     A dictionary containing
      * `distances`: A sparse, pairwise distance matrix between unique
        receptor configurations
-     * `cell_indices`: A dict of arrays, containing the `adata.obs_names`
+     * `cell_indices`: A dict of lists, containing the `adata.obs_names`
        (cell indices) for each row in the distance matrix.
 
     If `inplace` is `True`, this is added to `adata.uns[key_added]`.
@@ -353,7 +354,7 @@ def convert_str_array_dict_to_csr(str_array_dict: dict[str, np.ndarray[str]]) ->
     # Return or store results
     clonotype_distance_res = {
         "distances": clonotype_dist,
-        "cell_indices": convert_str_array_dict_to_csr(ctn.cell_indices),
+        "cell_indices": json.dumps(ctn.cell_indices),
     }
     if inplace:
         params.set_obs(key_added, clonotype_cluster_series)
@@ -547,7 +548,8 @@ def clonotype_network(
     graph.vs["node_id"] = np.arange(0, len(graph.vs))
 
     # store size in graph to be accessed by layout algorithms
-    clonotype_size = np.array([idx.size for idx in clonotype_res["cell_indices"].values()])
+    cell_indices = read_cell_indices(clonotype_res["cell_indices"])
+    clonotype_size = np.array([len(idx) for idx in cell_indices.values()])
     graph.vs["size"] = clonotype_size
     components = np.array(graph.decompose("weak"))
     component_node_count = np.array([len(component.vs) for component in components])
@@ -590,7 +592,7 @@ def clonotype_network(
     # Expand to cell coordinates to store in adata.obsm
     idx, coords = zip(
         *itertools.chain.from_iterable(
-            zip(clonotype_res["cell_indices"][str(node_id)], itertools.repeat(coord))
+            zip(cell_indices[str(node_id)], itertools.repeat(coord))
             for node_id, coord in zip(graph.vs["node_id"], coords, strict=False)  # type: ignore
         ),
         strict=False,
@@ -618,9 +620,10 @@ def _graph_from_coordinates(adata: AnnData, clonotype_key: str, basis: str) -> t
     """
     clonotype_res = adata.uns[clonotype_key]
     # map the cell-id to the corresponding row/col in the clonotype distance matrix
+    cell_indices = read_cell_indices(clonotype_res["cell_indices"])
     dist_idx, obs_names = zip(
         *itertools.chain.from_iterable(
-            zip(itertools.repeat(i), obs_names) for i, obs_names in clonotype_res["cell_indices"].items()
+            zip(itertools.repeat(i), obs_names) for i, obs_names in cell_indices.items()
         ),
         strict=False,
     )
diff --git a/src/scirpy/tl/_ir_query.py b/src/scirpy/tl/_ir_query.py
index 72a45679f..fbfa7cec8 100644
--- a/src/scirpy/tl/_ir_query.py
+++ b/src/scirpy/tl/_ir_query.py
@@ -7,10 +7,11 @@
 import numpy as np
 import pandas as pd
 from scanpy import logging
+import json
 
 from scirpy.ir_dist import MetricType, _get_metric_key
 from scirpy.ir_dist._clonotype_neighbors import ClonotypeNeighbors
-from scirpy.util import DataHandler, _is_na, tqdm
+from scirpy.util import DataHandler, _is_na, tqdm, read_cell_indices
 
 from ._clonotypes import _common_doc, _common_doc_parallelism, _doc_clonotype_definition, _validate_parameters
 
@@ -166,9 +167,9 @@ def ir_query(
     A dictionary containing
      * `distances`: A sparse distance matrix between unique receptor configurations
        in `adata` aund unique receptor configurations in `reference`.
-     * `cell_indices`: A dict of arrays, containing the the `adata.obs_names`
+     * `cell_indices`: A dict of lists, containing the the `adata.obs_names`
        (cell indices) for each row in the distance matrix.
-     * `cell_indices_reference`: A dict of arrays, containing the `reference.obs_names`
+     * `cell_indices_reference`: A dict of lists, containing the `reference.obs_names`
        for each column in the distance matrix.
 
     If `inplace` is `True`, this is added to `adata.uns[key_added]`.
@@ -206,8 +207,8 @@ def ir_query(
     # Return or store results
     clonotype_distance_res = {
         "distances": clonotype_dist,
-        "cell_indices": ctn.cell_indices,
-        "cell_indices_reference": ctn.cell_indices2,
+        "cell_indices": json.dumps(ctn.cell_indices),
+        "cell_indices_reference": json.dumps(ctn.cell_indices2),
     }
     if inplace:
         params.adata.uns[key_added] = clonotype_distance_res
@@ -284,10 +285,13 @@ def ir_query_annotate_df(
     res = params.adata.uns[query_key]
     dist = res["distances"]
 
+    cell_indices = read_cell_indices(res["cell_indices"])
+    cell_indices_reference = read_cell_indices(res["cell_indices_reference"])
+
     def get_pairs():
-        for i, query_cells in res["cell_indices"].items():
+        for i, query_cells in cell_indices.items():
             reference_cells = itertools.chain.from_iterable(
-                res["cell_indices_reference"][str(k)] for k in dist[int(i), :].indices
+                cell_indices_reference[str(k)] for k in dist[int(i), :].indices
             )
             yield from itertools.product(query_cells, reference_cells)
 
diff --git a/src/scirpy/util/__init__.py b/src/scirpy/util/__init__.py
index b46e0d336..789614579 100644
--- a/src/scirpy/util/__init__.py
+++ b/src/scirpy/util/__init__.py
@@ -16,6 +16,9 @@
 from scipy.sparse import issparse
 from tqdm.auto import tqdm
 
+from typing import Literal
+import json
+
 # reexport tqdm (here was previously a workaround for https://github.com/tqdm/tqdm/issues/1082)
 __all__ = ["tqdm"]
 
@@ -605,3 +608,18 @@ def _get_usable_cpus(n_jobs: int = 0, use_numba: bool = False):
         usable_cpus = min(usable_cpus, config.NUMBA_NUM_THREADS)
 
     return usable_cpus
+
+def read_cell_indices(cell_indices: Union[dict[str, np.ndarray[str]], str]) -> dict[str,list[str]]:
+    """
+    The datatype of the cell_indices Mapping (clonotype_id -> cell_ids) that is stored to the anndata.uns
+    attribute after the ´define_clonotype_clusters´ function has changed from dict[str, np.ndarray[str] to
+    str (json) due to performance considerations regarding the writing speed of the anndata object. But we still
+    want that older anndata objects with the dict[str, np.ndarray[str] datatype can be used. So we use this function
+    to read the cell_indices from the anndata object to support both formats.
+    """
+    if(isinstance(cell_indices, str)): # new format
+        return json.loads(cell_indices)
+    elif(isinstance(cell_indices, dict)): # old format
+        return {k: v.tolist() for k, v in cell_indices.items()}
+    else: # unsupported format
+        raise TypeError(f"Unsupported type for cell_indices: {type(cell_indices)}. Expected str (json) or dict[str, np.ndarray[str]].")

From 78124f1a3a9e4146b28c800816a6dd94e956568e Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 18 Sep 2024 17:28:03 +0000
Subject: [PATCH 3/5] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/scirpy/pl/_clonotypes.py      |  2 +-
 src/scirpy/tests/test_ir_query.py |  7 +++----
 src/scirpy/tl/_clonotypes.py      |  8 +++-----
 src/scirpy/tl/_ir_query.py        |  3 +--
 src/scirpy/util/__init__.py       | 19 ++++++++++---------
 5 files changed, 18 insertions(+), 21 deletions(-)

diff --git a/src/scirpy/pl/_clonotypes.py b/src/scirpy/pl/_clonotypes.py
index e6cb28ab0..5dc2a9b48 100644
--- a/src/scirpy/pl/_clonotypes.py
+++ b/src/scirpy/pl/_clonotypes.py
@@ -414,7 +414,7 @@ def _plot_clonotype_network_panel(
     color_by_n_cells,
 ):
     cell_indices = read_cell_indices(cell_indices)
-    
+
     colorbar_title = "mean per dot"
     pie_colors = None
     cat_colors = None
diff --git a/src/scirpy/tests/test_ir_query.py b/src/scirpy/tests/test_ir_query.py
index dfc10150e..7c33e69cf 100644
--- a/src/scirpy/tests/test_ir_query.py
+++ b/src/scirpy/tests/test_ir_query.py
@@ -5,8 +5,6 @@
 import pytest
 from mudata import MuData
 
-from scirpy.util import read_cell_indices
-
 from scirpy.pp import ir_dist
 from scirpy.tl._ir_query import (
     _reduce_json,
@@ -16,6 +14,7 @@
     ir_query_annotate,
     ir_query_annotate_df,
 )
+from scirpy.util import read_cell_indices
 
 
 @pytest.mark.parametrize("metric", ["identity", "levenshtein"])
@@ -34,10 +33,10 @@ def test_ir_query(adata_cdr3, adata_cdr3_2, metric, key1, key2):
 
     tmp_key2 = f"ir_query_TESTDB_aa_{metric}" if key2 is None else key2
     tmp_ad = adata_cdr3.mod["airr"] if isinstance(adata_cdr3, MuData) else adata_cdr3
-    
+
     cell_indices = read_cell_indices(tmp_ad.uns[tmp_key2]["cell_indices"])
     cell_indices_reference = read_cell_indices(tmp_ad.uns[tmp_key2]["cell_indices_reference"])
-    
+
     assert tmp_ad.uns[tmp_key2]["distances"].shape == (4, 3)
     assert len(cell_indices) == 4
     assert len(cell_indices_reference) == 3
diff --git a/src/scirpy/tl/_clonotypes.py b/src/scirpy/tl/_clonotypes.py
index 0a0aafa19..2b3a60c4d 100644
--- a/src/scirpy/tl/_clonotypes.py
+++ b/src/scirpy/tl/_clonotypes.py
@@ -1,4 +1,5 @@
 import itertools
+import json
 import random
 from collections.abc import Sequence
 from typing import Literal, cast
@@ -9,7 +10,6 @@
 import scipy.sparse as sp
 from anndata import AnnData
 from scanpy import logging
-import json
 
 from scirpy.ir_dist import MetricType, _get_metric_key
 from scirpy.ir_dist._clonotype_neighbors import ClonotypeNeighbors
@@ -343,7 +343,7 @@ def convert_str_array_dict_to_csr(str_array_dict: dict[str, np.ndarray[str]]) ->
         for key_str, value in str_array_dict.items():
             key = int(key_str)
             data_arrays[key] = value.astype(int)
-            indices_arrays[key] = np.array(range(0,len(value)))
+            indices_arrays[key] = np.array(range(0, len(value)))
             nnz_array[key] = len(value)
 
         data = np.concatenate(data_arrays)
@@ -622,9 +622,7 @@ def _graph_from_coordinates(adata: AnnData, clonotype_key: str, basis: str) -> t
     # map the cell-id to the corresponding row/col in the clonotype distance matrix
     cell_indices = read_cell_indices(clonotype_res["cell_indices"])
     dist_idx, obs_names = zip(
-        *itertools.chain.from_iterable(
-            zip(itertools.repeat(i), obs_names) for i, obs_names in cell_indices.items()
-        ),
+        *itertools.chain.from_iterable(zip(itertools.repeat(i), obs_names) for i, obs_names in cell_indices.items()),
         strict=False,
     )
     dist_idx_lookup = pd.DataFrame(index=obs_names, data=dist_idx, columns=["dist_idx"])
diff --git a/src/scirpy/tl/_ir_query.py b/src/scirpy/tl/_ir_query.py
index fbfa7cec8..89bf5c975 100644
--- a/src/scirpy/tl/_ir_query.py
+++ b/src/scirpy/tl/_ir_query.py
@@ -7,11 +7,10 @@
 import numpy as np
 import pandas as pd
 from scanpy import logging
-import json
 
 from scirpy.ir_dist import MetricType, _get_metric_key
 from scirpy.ir_dist._clonotype_neighbors import ClonotypeNeighbors
-from scirpy.util import DataHandler, _is_na, tqdm, read_cell_indices
+from scirpy.util import DataHandler, _is_na, read_cell_indices, tqdm
 
 from ._clonotypes import _common_doc, _common_doc_parallelism, _doc_clonotype_definition, _validate_parameters
 
diff --git a/src/scirpy/util/__init__.py b/src/scirpy/util/__init__.py
index 789614579..d9924c60f 100644
--- a/src/scirpy/util/__init__.py
+++ b/src/scirpy/util/__init__.py
@@ -1,9 +1,10 @@
 import contextlib
+import json
 import os
 import warnings
 from collections.abc import Callable, Mapping, Sequence
 from textwrap import dedent
-from typing import Any, Optional, Union, cast, overload
+from typing import Any, Literal, Optional, Union, cast, overload
 
 import awkward as ak
 import numpy as np
@@ -16,9 +17,6 @@
 from scipy.sparse import issparse
 from tqdm.auto import tqdm
 
-from typing import Literal
-import json
-
 # reexport tqdm (here was previously a workaround for https://github.com/tqdm/tqdm/issues/1082)
 __all__ = ["tqdm"]
 
@@ -609,7 +607,8 @@ def _get_usable_cpus(n_jobs: int = 0, use_numba: bool = False):
 
     return usable_cpus
 
-def read_cell_indices(cell_indices: Union[dict[str, np.ndarray[str]], str]) -> dict[str,list[str]]:
+
+def read_cell_indices(cell_indices: dict[str, np.ndarray[str]] | str) -> dict[str, list[str]]:
     """
     The datatype of the cell_indices Mapping (clonotype_id -> cell_ids) that is stored to the anndata.uns
     attribute after the ´define_clonotype_clusters´ function has changed from dict[str, np.ndarray[str] to
@@ -617,9 +616,11 @@ def read_cell_indices(cell_indices: Union[dict[str, np.ndarray[str]], str]) -> d
     want that older anndata objects with the dict[str, np.ndarray[str] datatype can be used. So we use this function
     to read the cell_indices from the anndata object to support both formats.
     """
-    if(isinstance(cell_indices, str)): # new format
+    if isinstance(cell_indices, str):  # new format
         return json.loads(cell_indices)
-    elif(isinstance(cell_indices, dict)): # old format
+    elif isinstance(cell_indices, dict):  # old format
         return {k: v.tolist() for k, v in cell_indices.items()}
-    else: # unsupported format
-        raise TypeError(f"Unsupported type for cell_indices: {type(cell_indices)}. Expected str (json) or dict[str, np.ndarray[str]].")
+    else:  # unsupported format
+        raise TypeError(
+            f"Unsupported type for cell_indices: {type(cell_indices)}. Expected str (json) or dict[str, np.ndarray[str]]."
+        )

From bca630e0d9ac170f935d377b1aabf592ec8f0148 Mon Sep 17 00:00:00 2001
From: felixpetschko <felixpetschko@gmail.com>
Date: Wed, 18 Sep 2024 20:15:43 +0200
Subject: [PATCH 4/5] removed unused conversion function

---
 src/scirpy/tl/_clonotypes.py | 18 ------------------
 1 file changed, 18 deletions(-)

diff --git a/src/scirpy/tl/_clonotypes.py b/src/scirpy/tl/_clonotypes.py
index 0a0aafa19..fdb1491a5 100644
--- a/src/scirpy/tl/_clonotypes.py
+++ b/src/scirpy/tl/_clonotypes.py
@@ -333,24 +333,6 @@ def define_clonotype_clusters(
     clonotype_cluster_series = pd.Series(values, index=idx).reindex(params.adata.obs_names)
     clonotype_cluster_size_series = clonotype_cluster_series.groupby(clonotype_cluster_series).transform("count")
 
-    def convert_str_array_dict_to_csr(str_array_dict: dict[str, np.ndarray[str]]) -> sp.csr_matrix:
-        num_rows = len(str_array_dict)
-
-        data_arrays = [np.array([])] * num_rows
-        indices_arrays = [np.array([])] * num_rows
-        nnz_array = np.zeros(num_rows)
-
-        for key_str, value in str_array_dict.items():
-            key = int(key_str)
-            data_arrays[key] = value.astype(int)
-            indices_arrays[key] = np.array(range(0,len(value)))
-            nnz_array[key] = len(value)
-
-        data = np.concatenate(data_arrays)
-        indices = np.concatenate(indices_arrays)
-        indptr = np.concatenate([np.array([0]), np.cumsum(nnz_array)])
-        return sp.csr_matrix((data, indices, indptr))
-
     # Return or store results
     clonotype_distance_res = {
         "distances": clonotype_dist,

From 6be5b2aeb89ded0cc943635657714fdafc9d3394 Mon Sep 17 00:00:00 2001
From: Gregor Sturm <mail@gregor-sturm.de>
Date: Wed, 6 Nov 2024 20:22:24 +0100
Subject: [PATCH 5/5] Update CHANGELOG

---
 CHANGELOG.md | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 436c7dc0c..0436fcf8d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -10,9 +10,17 @@ and this project adheres to [Semantic Versioning][].
 
 ## [Unreleased]
 
+### Backwards-incompatible changes
+
+-   The format of storing the results of `tl.define_clonotypes`/`tl.define_clonotype_clusters` in `adata.uns` has changed.
+    Older versions of Scirpy won't be able to run downstream functions (e.g. `tl.clonotype_network`) on AnnData objects
+    created with Scirpy v0.20 or later. This change was necessary to speed up writing results to `h5ad` when working
+    with large datasets ([#556](https://github.com/scverse/scirpy/pull/556)).
+
 ### Documentation
 
 -   Add a tutorial for BCR analysis with Scirpy ([#542](https://github.com/scverse/scirpy/pull/542)).
+-   Fix typo in `pp.index_chains` methods description ([#570](https://github.com/scverse/scirpy/pull/570))
 
 ## v0.19.0