From 6f3fb5544f2e7d55cc7aa83d8af481ca13e615f6 Mon Sep 17 00:00:00 2001
From: Julianus Pfeuffer <8102638+jpfeuffer@users.noreply.github.com>
Date: Thu, 15 Oct 2026 17:16:39 +0200
Subject: [PATCH 1/7] Require Zarr Python 3 and modern Xarray

Preserve the default Zarr format 2 storage, support current string codecs and store types, and replace the incompatible deprecated BGEN rechunker backend with Xarray and Dask. Update the lockfile, minimum-version CI, regression tests and documentation.

Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
---
 .github/workflows/build.yml             |  12 +-
 docs/changelog.rst                      |  10 +-
 docs/user_guide.rst                     |  16 +-
 pyproject.toml                          |  12 +-
 sgkit/io/bgen/bgen_reader.py            |  82 ++---
 sgkit/io/dataset.py                     |  34 +-
 sgkit/io/plink/plink_reader.py          |   5 +-
 sgkit/io/plink/plink_writer.py          |   5 +-
 sgkit/tests/io/bgen/test_bgen_reader.py |  27 +-
 sgkit/tests/io/test_dataset.py          |  58 +++-
 sgkit/tests/io/test_vcf2zarr_compat.py  |  18 +-
 sgkit/tests/test_association.py         |   6 +-
 sgkit/tests/test_regenie.py             |   6 +-
 sgkit/utils.py                          |   8 -
 uv.lock                                 | 402 +++++++++++++-----------
 15 files changed, 376 insertions(+), 325 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index b3c21f06c..e688b7587 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -41,14 +41,11 @@ jobs:
       with:
         token: ${{ secrets.CODECOV_TOKEN }}
 
-  test-zarr-version:
-    name: Test Zarr Python v3
+  test-xarray-minimum:
+    name: Test minimum Xarray
     # Scheduled runs only on the origin org
     if: (github.event_name == 'schedule' && github.repository_owner == 'sgkit-dev') || (github.event_name != 'schedule')
     runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        zarr: [">=3"]
     steps:
       - uses: actions/checkout@v7
       - uses: actions/setup-python@v7
@@ -63,10 +60,9 @@ jobs:
       - name: Install dependencies
         run: |
           uv sync --locked --all-extras --group test --no-default-groups --python 3.11
-      - name: Install zarr${{ matrix.zarr }}
+      - name: Install minimum supported Xarray
         run: |
-          uv pip install --python .venv --pre 'zarr${{ matrix.zarr }}'
-          uv pip uninstall --python .venv bio2zarr  # TODO: remove when bio2zarr supports Zarr Python 3
+          uv pip install --python .venv 'xarray==2026.9.0'
       - name: Run tests
         run: |
           uv run --no-sync pytest
diff --git a/docs/changelog.rst b/docs/changelog.rst
index 91b574ec8..b2f98dfb3 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -11,8 +11,14 @@ Changelog
 .. New Features
 .. ~~~~~~~~~~~~
 
-.. Breaking changes
-.. ~~~~~~~~~~~~~~~~
+Breaking changes
+~~~~~~~~~~~~~~~~
+
+- Require Zarr Python >= 3 and Xarray >= 2026.9.0. The default on-disk Zarr
+  format remains 2. (:issue:`1355`)
+- Remove the incompatible rechunker dependency from the BGEN extra. The
+  deprecated BGEN conversion functions now use Xarray and Dask; ``max_mem``
+  and ``tempdir`` no longer control rechunking.
 
 Deprecations
 ~~~~~~~~~~~~
diff --git a/docs/user_guide.rst b/docs/user_guide.rst
index d5b246980..76cacca96 100644
--- a/docs/user_guide.rst
+++ b/docs/user_guide.rst
@@ -58,7 +58,15 @@ Similarly, the function :func:`sgkit.save_dataset` can be used to save the datas
 This can be used to save a newly-loaded dataset, or a dataset with new variables that are the
 result of running genetic methods on the data, so it can be loaded again later.
 
-By default, Zarr datasets created by sgkit (and Xarray) have `consolidated metadata <http://xarray.pydata.org/en/stable/user-guide/io.html#consolidated-metadata>`_,
+Sgkit requires Zarr Python >= 3 and Xarray >= 2026.9.0, but
+:func:`sgkit.save_dataset` continues to write **Zarr format 2** by default.
+The Python package version does not determine the on-disk format.
+Pass ``zarr_format=3`` to opt into format 3; :func:`sgkit.load_dataset`
+can read either format.
+The Xarray minimum includes support for the native NumPy string dtype returned
+by recent Zarr releases, preserving string-array chunking on load.
+
+By default, Zarr format 2 datasets created by sgkit have `consolidated metadata <http://xarray.pydata.org/en/stable/user-guide/io.html#consolidated-metadata>`_,
 which makes opening the dataset faster.
 
 BGEN
@@ -71,6 +79,12 @@ The :func:`sgkit.io.bgen.bgen_to_zarr` function converts a ``bgen`` file to Zarr
 files stored in sgkit's Xarray data representation, which can then be opened
 as a :class:`xarray.Dataset`.
 
+The deprecated BGEN conversion functions now rechunk with Xarray and Dask,
+without the Zarr Python 2-only rechunker package. They still write Zarr format 2
+and preserve probability encoding and packing. The ``max_mem`` and ``tempdir``
+parameters are retained for compatibility but no longer have an effect; configure
+chunk sizes and the Dask scheduler to control memory use.
+
 PLINK
 -----
 
diff --git a/pyproject.toml b/pyproject.toml
index 8dde5ed1d..dfd0ab5f1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -22,10 +22,10 @@ requires-python = ">=3.11"
 dependencies = [
   "numpy >= 2.3.5; sys_platform == \"darwin\"", # Apple ARM chip error
   "numpy >= 2.0; sys_platform != \"darwin\"",
-  "xarray < 2025.03.1",
+  "xarray >= 2026.9.0",
   "dask[array,dataframe] >= 2022.01.0, <= 2024.8.0",
   "scipy < 1.16",
-  "zarr >= 2.10.0, != 2.11.0, != 2.11.1, != 2.11.2, < 3",
+  "zarr >= 3",
   "numba",
   "fsspec != 2021.6.*",
   "scikit-learn",
@@ -41,7 +41,7 @@ content-type = "text/x-rst"
 
 [project.optional-dependencies]
 plink = ["partd", "bed-reader"]
-bgen = ["rechunker", "cbgen > 1.0.5"]
+bgen = ["cbgen > 1.0.5"]
 
 [dependency-groups]
 test = [
@@ -55,7 +55,7 @@ test = [
   "scikit-allel",
   "statsmodels",
   "msprime>=1.0",
-  "bio2zarr[vcf]; platform_system != \"Windows\"",
+  "bio2zarr[vcf] >= 0.2; platform_system != \"Windows\"",
   "yarl",
   "matplotlib",
   "networkx",
@@ -193,10 +193,6 @@ ignore_missing_imports = true
 module = ["cbgen.*"]
 ignore_missing_imports = true
 
-[[tool.mypy.overrides]]
-module = ["rechunker.*"]
-ignore_missing_imports = true
-
 [[tool.mypy.overrides]]
 module = ["bed_reader.*"]
 ignore_missing_imports = true
diff --git a/sgkit/io/bgen/bgen_reader.py b/sgkit/io/bgen/bgen_reader.py
index 6fa44bfe3..e9212d229 100644
--- a/sgkit/io/bgen/bgen_reader.py
+++ b/sgkit/io/bgen/bgen_reader.py
@@ -1,20 +1,9 @@
 """BGEN reader implementation (using bgen_reader)"""
 import logging
-import tempfile
 import time
 import warnings
 from pathlib import Path
-from typing import (
-    Any,
-    Dict,
-    Hashable,
-    List,
-    Mapping,
-    MutableMapping,
-    Optional,
-    Tuple,
-    Union,
-)
+from typing import Any, Dict, Hashable, List, Mapping, Optional, Tuple, Union
 
 import dask
 import dask.array as da
@@ -23,10 +12,9 @@
 import numpy as np
 import pandas as pd
 import xarray as xr
-import zarr
 from cbgen import bgen_file, bgen_metafile
-from rechunker import api as rechunker_api
 from xarray import Dataset
+from zarr.storage import StoreLike
 
 from sgkit import create_genotype_dosage_dataset, variables
 from sgkit.io.utils import dataframe_to_dict, encode_contigs
@@ -355,9 +343,7 @@ def encode_variables(
 ) -> Dict[Hashable, Dict[str, Any]]:
     encoding = {}
     for v in ds:
-        e = {}
-        if compressor is not None:
-            e.update({"compressor": compressor})
+        e = {"compressors": compressor}
         if v in GT_DATA_VARS:
             e.update({"chunks": (chunk_length, chunk_width) + ds[v].shape[2:]})
         if probability_dtype is not None and v == "call_genotype_probability":
@@ -422,7 +408,7 @@ def unpack_variables(ds: Dataset, dtype: DType = "float32") -> Dataset:
 
 def rechunk_bgen(
     ds: Dataset,
-    output: Union[PathType, MutableMapping[str, bytes]],
+    output: StoreLike,
     *,
     chunk_length: int = 10_000,
     chunk_width: int = 1_000,
@@ -434,12 +420,11 @@ def rechunk_bgen(
 ) -> Dataset:
     """Rechunk BGEN dataset as Zarr.
 
-    This function will use the algorithm https://rechunker.readthedocs.io/en/latest/
-    to rechunk certain fields in a provided Dataset for better downstream performance.
-    Depending on the system memory available (and the `max_mem` setting) this
-    rechunking may occur without the need of any intermediate data store. Otherwise,
-    approximately as much disk space is required as was needed to store the original
-    BGEN data. Experiments show that this Zarr representation is ~20% larger even
+    This function uses Xarray and Dask to rechunk a Dataset for better downstream
+    performance and writes Zarr format 2. It no longer uses rechunker, which does
+    not support Zarr Python 3. Memory usage depends on the input and output chunks
+    and the Dask scheduler; no intermediate store is created.
+    Experiments show that this Zarr representation is ~20% larger even
     with all available optimizations and fairly aggressive compression (i.e. the
     default `clevel` 7).
 
@@ -448,7 +433,7 @@ def rechunk_bgen(
     generated based on the final, serialized Zarr data.
 
     .. deprecated:: 0.11.0
-       Using rechunker for rechunking in sgkit is deprecated, please use the the
+       This conversion helper is deprecated, please use the
        `Xarray chunk <https://docs.xarray.dev/en/stable/generated/xarray.Dataset.chunk.html#xarray.Dataset.chunk>`_
        function directly.
 
@@ -469,8 +454,7 @@ def rechunk_bgen(
         Setting this parameter results in a loss of precision. If None, probabilities
         will not be altered when stored.
     max_mem
-        The amount of memory (in bytes) that workers are allowed to use. A string
-        (e.g. 100MB) can also be used.
+        Deprecated and no longer used. Memory is managed by Dask.
     pack
         Whether or not to optimize variable representations by removing unnecessary
         dimensions and elements. This includes storing 2 genotypes instead of 3, omitting
@@ -478,8 +462,7 @@ def rechunk_bgen(
         the above are restored in the resulting Dataset at the expense of extra
         computations on read.
     tempdir
-        Temporary directory where intermediate files are stored. The default None means
-        use the system default temporary directory.
+        Deprecated and no longer used. No intermediate store is created.
 
     Warnings
     --------
@@ -493,10 +476,17 @@ def rechunk_bgen(
         The rechunked dataset.
     """
     warnings.warn(
-        "Using rechunker for rechunking in sgkit is deprecated, please use the the Xarray 'chunk' function directly.",
+        "rechunk_bgen is deprecated, please use Xarray 'chunk' and sgkit.save_dataset directly.",
         DeprecationWarning,
         stacklevel=2,
     )
+    if max_mem != "4GB" or tempdir is not None:
+        warnings.warn(
+            "max_mem and tempdir no longer control BGEN rechunking; "
+            "memory is managed by Dask and no intermediate store is created.",
+            FutureWarning,
+            stacklevel=2,
+        )
 
     if isinstance(output, Path):
         output = str(output)
@@ -514,28 +504,8 @@ def rechunk_bgen(
         compressor=compressor,
         probability_dtype=probability_dtype,
     )
-    target_chunks = {
-        var: encoding[var]["chunks"] for var in encoding if "chunks" in encoding[var]
-    }
-    target_options = {
-        var: {k: v for k, v in encoding[var].items() if k != "chunks"}
-        for var in encoding
-    }
-    with tempfile.TemporaryDirectory(
-        prefix="bgen_to_zarr_", suffix=".zarr", dir=tempdir
-    ) as tmpdir:
-        rechunked = rechunker_api.rechunk(
-            ds,
-            max_mem=max_mem,
-            target_chunks=target_chunks,
-            target_store=output,
-            target_options=target_options,
-            temp_store=tmpdir,
-            executor="dask",
-        )
-        rechunked.execute()
-
-    zarr.consolidate_metadata(output)
+    ds = ds.chunk({"variants": chunk_length, "samples": chunk_width})
+    ds.to_zarr(output, encoding=encoding, zarr_format=2, consolidated=True, mode="w-")
 
     ds = xr.open_zarr(output, concat_characters=False)  # type: ignore[no-untyped-call]
     if pack:
@@ -546,7 +516,7 @@ def rechunk_bgen(
 
 def bgen_to_zarr(
     input: PathType,
-    output: Union[PathType, MutableMapping[str, bytes]],
+    output: StoreLike,
     region: Optional[Mapping[Hashable, Any]] = None,
     chunk_length: int = 10_000,
     chunk_width: int = 1_000,
@@ -590,8 +560,7 @@ def bgen_to_zarr(
         Setting this parameter results in a loss of precision. If None, probabilities
         will not be altered when stored.
     max_mem
-        The amount of memory (in bytes) that workers are allowed to use. A string
-        (e.g. 100MB) can also be used.
+        Deprecated and no longer used. Memory is managed by Dask.
     pack
         Whether or not to optimize variable representations by removing unnecessary
         dimensions and elements. This includes storing 2 genotypes instead of 3, omitting
@@ -599,8 +568,7 @@ def bgen_to_zarr(
         the above are restored in the resulting Dataset at the expense of extra
         computations on read.
     tempdir
-        Temporary directory where intermediate files are stored. The default None means
-        use the system default temporary directory.
+        Deprecated and no longer used. No intermediate store is created.
 
     Warnings
     --------
diff --git a/sgkit/io/dataset.py b/sgkit/io/dataset.py
index 4f5226168..514007202 100644
--- a/sgkit/io/dataset.py
+++ b/sgkit/io/dataset.py
@@ -1,16 +1,14 @@
-from typing import Any, Dict, MutableMapping, Optional, Union
+from typing import Any, Dict, Optional
 
 import numcodecs
 import xarray as xr
 from xarray import Dataset
-
-from sgkit.typing import PathType
-from sgkit.utils import has_keyword
+from zarr.storage import StoreLike
 
 
 def save_dataset(
     ds: Dataset,
-    store: Union[PathType, MutableMapping[str, bytes]],
+    store: StoreLike,
     storage_options: Optional[Dict[str, str]] = None,
     auto_rechunk: Optional[bool] = None,
     zarr_format: int = 2,
@@ -32,6 +30,9 @@ def save_dataset(
     auto_rechunk:
         If True, automatically rechunk the dataset to uniform chunks before saving,
         if necessary. This is required for Zarr, but can be expensive. Defaults to False.
+    zarr_format:
+        On-disk Zarr format, either 2 or 3. Defaults to 2 for compatibility with
+        existing datasets, even though sgkit requires Zarr Python 3.
     kwargs
         Additional arguments to pass to :meth:`xarray.Dataset.to_zarr`.
     """
@@ -41,13 +42,14 @@ def save_dataset(
         # Workaround for https://github.com/pydata/xarray/issues/4380
         ds[v].encoding.pop("chunks", None)
 
-        # Remove VLenUTF8 from filters to avoid double encoding error https://github.com/pydata/xarray/issues/3476
-        filters = ds[v].encoding.get("filters", None)
-        var_len_str_codec = numcodecs.VLenUTF8()
-        if filters is not None and var_len_str_codec in filters:
-            filters = list(filters)
-            filters.remove(var_len_str_codec)
-            ds[v].encoding["filters"] = filters
+        # Xarray writes native NumPy strings as fixed-width Unicode in format 2.
+        # A VLenUTF8 filter inherited from a variable-length array is then invalid.
+        dtype = ds[v].encoding.get("dtype", ds[v].dtype)
+        filters = ds[v].encoding.get("filters")
+        if getattr(dtype, "kind", None) == "T" and filters is not None:
+            ds[v].encoding["filters"] = [
+                f for f in filters if f != numcodecs.VLenUTF8()
+            ]
 
     if auto_rechunk:
         # This logic for checking if rechunking is necessary is
@@ -66,9 +68,9 @@ def save_dataset(
 
     # Catch unequal chunking errors to provide a more helpful error message
     try:
-        if has_keyword(ds.to_zarr, "zarr_format"):  # from xarray v2024.10.0
-            kwargs["zarr_format"] = zarr_format
-        ds.to_zarr(store, storage_options=storage_options, **kwargs)
+        ds.to_zarr(
+            store, storage_options=storage_options, zarr_format=zarr_format, **kwargs
+        )
     except ValueError as e:
         if "Zarr requires uniform chunk sizes" in str(
             e
@@ -82,7 +84,7 @@ def save_dataset(
 
 
 def load_dataset(
-    store: Union[PathType, MutableMapping[str, bytes]],
+    store: StoreLike,
     storage_options: Optional[Dict[str, str]] = None,
     **kwargs: Any,
 ) -> Dataset:
diff --git a/sgkit/io/plink/plink_reader.py b/sgkit/io/plink/plink_reader.py
index b6da1c012..63d6d5ee1 100644
--- a/sgkit/io/plink/plink_reader.py
+++ b/sgkit/io/plink/plink_reader.py
@@ -1,6 +1,6 @@
 """PLINK 1.9 reader implementation"""
 from pathlib import Path
-from typing import Any, Dict, List, MutableMapping, Optional, Tuple, Union
+from typing import Any, Dict, List, Optional, Tuple, Union
 
 import dask
 import dask.array as da
@@ -9,6 +9,7 @@
 from bed_reader import open_bed
 from dask.dataframe import DataFrame
 from xarray import Dataset
+from zarr.storage import StoreLike
 
 from sgkit import create_genotype_call_dataset, save_dataset
 from sgkit.io.utils import dataframe_to_dict
@@ -317,7 +318,7 @@ def plink_to_zarr(
     bed_path: Optional[PathType] = None,
     bim_path: Optional[PathType] = None,
     fam_path: Optional[PathType] = None,
-    output: Union[PathType, MutableMapping[str, bytes]],
+    output: StoreLike,
     chunks: Union[str, int, tuple] = "auto",
     fam_sep: str = " ",
     bim_sep: str = "\t",
diff --git a/sgkit/io/plink/plink_writer.py b/sgkit/io/plink/plink_writer.py
index 42939b492..6c380b930 100644
--- a/sgkit/io/plink/plink_writer.py
+++ b/sgkit/io/plink/plink_writer.py
@@ -1,8 +1,9 @@
-from typing import MutableMapping, Optional, Union
+from typing import Optional
 
 import numpy as np
 from bed_reader import to_bed
 from xarray import Dataset
+from zarr.storage import StoreLike
 
 from sgkit import load_dataset
 from sgkit.accelerate import numba_guvectorize
@@ -137,7 +138,7 @@ def write_plink(
 
 
 def zarr_to_plink(
-    input: Union[PathType, MutableMapping[str, bytes]],
+    input: StoreLike,
     *,
     path: Optional[PathType] = None,
     bed_path: Optional[PathType] = None,
diff --git a/sgkit/tests/io/bgen/test_bgen_reader.py b/sgkit/tests/io/bgen/test_bgen_reader.py
index be8c2bb57..428014cda 100644
--- a/sgkit/tests/io/bgen/test_bgen_reader.py
+++ b/sgkit/tests/io/bgen/test_bgen_reader.py
@@ -1,16 +1,13 @@
 from pathlib import Path
 from typing import Any, Tuple
 
+import numcodecs
 import numpy as np
 import numpy.testing as npt
 import pytest
 import xarray as xr
 import zarr
-from packaging.version import Version
-
-pytestmark = pytest.mark.skipif(
-    Version(zarr.__version__).major >= 3, reason="Rechunking fails for Zarr Python 3"
-)
+from zarr.storage import MemoryStore
 
 from sgkit.io.bgen.bgen_reader import (
     GT_DATA_VARS,
@@ -230,6 +227,26 @@ def test_rechunk_bgen__target_chunks(shared_datadir, tmp_path, target_chunks):
     )
     for v in GT_DATA_VARS:
         assert dsr[v].data.chunksize[:2] == target_chunks
+    assert zarr.open_group(store, mode="r").metadata.zarr_format == 2
+
+
+@pytest.mark.parametrize("compressor", [None, numcodecs.Blosc(cname="zstd", clevel=7)])
+def test_rechunk_bgen__compressor(shared_datadir, tmp_path, compressor):
+    _, _, store = _rechunk_bgen(shared_datadir, tmp_path, compressor=compressor)
+    array = zarr.open_group(store, mode="r")["call_genotype_probability"]
+    assert array.compressors == (() if compressor is None else (compressor,))
+
+
+def test_rechunk_bgen__memory_store(shared_datadir):
+    ds = read_bgen(shared_datadir / "example.bgen")
+    store = MemoryStore()
+    dsr = rechunk_bgen(ds, store, probability_dtype=None, pack=False)
+    xr.testing.assert_allclose(ds.compute(), dsr.compute())
+
+
+def test_rechunk_bgen__legacy_memory_options(shared_datadir, tmp_path):
+    with pytest.warns(FutureWarning, match="max_mem and tempdir no longer control"):
+        _rechunk_bgen(shared_datadir, tmp_path, max_mem="1MB", tempdir=tmp_path)
 
 
 def test_rechunk_from_zarr__self_consistent(shared_datadir, tmp_path):
diff --git a/sgkit/tests/io/test_dataset.py b/sgkit/tests/io/test_dataset.py
index ce3ce6210..ba95c073d 100644
--- a/sgkit/tests/io/test_dataset.py
+++ b/sgkit/tests/io/test_dataset.py
@@ -1,10 +1,9 @@
-from typing import MutableMapping
-
+import numcodecs
 import pytest
 import xarray as xr
 import zarr
-from packaging.version import Version
 from xarray import Dataset
+from zarr.storage import MemoryStore
 
 from sgkit import load_dataset, save_dataset
 from sgkit.testing import simulate_genotype_call_dataset
@@ -26,6 +25,7 @@ def test_save_and_load_dataset(tmp_path, is_path):
         path = str(path)
     ds = simulate_genotype_call_dataset(n_variant=10, n_sample=10)
     save_dataset(ds, path)
+    assert zarr.open_group(path, mode="r").metadata.zarr_format == 2
     ds2 = load_dataset(path)
     assert_identical(ds, ds2)
 
@@ -37,30 +37,64 @@ def test_save_and_load_dataset(tmp_path, is_path):
     assert_identical(ds, load_dataset(path2))
 
 
-def test_save_and_load_dataset__mutable_mapping():
-    store: MutableMapping[str, bytes] = {}
+@pytest.mark.parametrize("store_factory", [dict, MemoryStore])
+def test_save_and_load_dataset__memory_store(store_factory):
+    store = store_factory()
     ds = simulate_genotype_call_dataset(n_variant=10, n_sample=10)
     save_dataset(ds, store)
     ds2 = load_dataset(store)
     assert_identical(ds, ds2)
 
     # save and load again to test https://github.com/pydata/xarray/issues/4386
-    store2: MutableMapping[str, bytes] = {}
+    store2 = store_factory()
     save_dataset(ds2, store2)
     assert_identical(ds, load_dataset(store2))
 
 
-def test_save_unequal_chunks_error():
+def test_save_and_load_dataset__format_3(tmp_path):
+    ds = xr.Dataset(
+        {
+            "value": ("variants", [0, 1, -1]),
+            "value_mask": ("variants", [False, False, True]),
+        }
+    ).chunk({"variants": 2})
+    store = tmp_path / "ds.zarr"
+    save_dataset(ds, store, zarr_format=3, consolidated=False)
+    assert zarr.open_group(store, mode="r").metadata.zarr_format == 3
+    assert_identical(ds, load_dataset(store, consolidated=False))
+
+
+@pytest.mark.parametrize("dtype", [object, "T"])
+def test_save_dataset__vlen_utf8_filter(dtype):
+    ds = xr.Dataset({"text": ("variants", ["a", "abc"])}).astype(dtype)
+    ds["text"].encoding["filters"] = [numcodecs.VLenUTF8()]
+    store = MemoryStore()
+    save_dataset(ds, store)
+    assert ds["text"].encoding["filters"] == (
+        [] if dtype == "T" else [numcodecs.VLenUTF8()]
+    )
+    xr.testing.assert_identical(ds, load_dataset(store))
+
+
+def test_save_dataset__invalid_encoding():
+    ds = simulate_genotype_call_dataset(n_variant=10, n_sample=10)
+    with pytest.raises(ValueError, match="unexpected encoding parameters"):
+        save_dataset(ds, {}, encoding={"variant_position": {"invalid": True}})
+
+
+def test_save_unequal_chunks_error(tmp_path):
     # Make all dimensions the same size for ease of testing
     ds = simulate_genotype_call_dataset(
         n_variant=10, n_sample=10, n_ploidy=10, n_allele=10, n_contig=10
     )
     # Normal zarr errors shouldn't be caught
+    store = tmp_path / "array.zarr"
+    zarr.create_array(store=store, shape=(1,), dtype="i1", zarr_format=2)
     with pytest.raises(
         (FileExistsError, ValueError),
         match="(path '' contains an array|is not empty|contains data)",
     ):
-        save_dataset(ds, {".zarray": ""})
+        save_dataset(ds, store)
 
     # Make the dataset have unequal chunk sizes across all dimensions
     ds = ds.chunk({dim: (1, 3, 5, 1) for dim in ds.sizes})
@@ -79,16 +113,14 @@ def test_save_unequal_chunks_error():
         save_dataset(ds, {})
 
 
-@pytest.mark.skipif(
-    Version(zarr.__version__).major >= 3, reason="Fails for Zarr Python 3"
-)
-def test_save_auto_rechunk():
+@pytest.mark.parametrize("chunks", [(1, 3, 5, 1), (4, 6)])
+def test_save_auto_rechunk(chunks):
     # Make all dimensions the same size for ease of testing
     ds = simulate_genotype_call_dataset(
         n_variant=10, n_sample=10, n_ploidy=10, n_allele=10, n_contig=10
     )
     # Make the dataset have unequal chunk sizes across all dimensions
-    ds = ds.chunk({dim: (1, 3, 5, 1) for dim in ds.sizes})
+    ds = ds.chunk({dim: chunks for dim in ds.sizes})
 
     # Default is to not rechunk
     with pytest.raises(
diff --git a/sgkit/tests/io/test_vcf2zarr_compat.py b/sgkit/tests/io/test_vcf2zarr_compat.py
index 7f185763e..be0b62b57 100644
--- a/sgkit/tests/io/test_vcf2zarr_compat.py
+++ b/sgkit/tests/io/test_vcf2zarr_compat.py
@@ -1,5 +1,6 @@
 import numpy as np
 import pytest
+import xarray as xr
 
 pytest.importorskip("bio2zarr")
 from bio2zarr import vcf
@@ -15,7 +16,6 @@
 
 from sgkit import load_dataset, save_dataset
 from sgkit.model import get_contigs, get_filters, num_contigs
-from sgkit.tests.io.test_dataset import assert_identical
 
 
 @pytest.mark.filterwarnings("ignore::xarray.coding.variables.SerializationWarning")
@@ -29,9 +29,10 @@ def test_vcf2zarr_compat(shared_datadir, tmp_path):
         variants_chunk_size=5,
         samples_chunk_size=2,
         worker_processes=0,
+        zarr_format=2,
     )
 
-    ds = load_dataset(vcz_path)
+    ds = load_dataset(vcz_path, consolidated=False)
 
     assert_array_equal(ds["filter_id"], ["PASS", "s50", "q10"])
     assert_array_equal(get_filters(ds), ["PASS", "s50", "q10"])  # utility function
@@ -164,13 +165,13 @@ def test_vcf2zarr_compat(shared_datadir, tmp_path):
         ],
     )
     assert ds["variant_allele"].chunks[0][0] == 5
-    assert ds["variant_allele"].dtype == "O"
+    assert ds["variant_allele"].dtype.kind in ("O", "T")
     assert_array_equal(
         ds["variant_id"].values.tolist(),
         [sm, sm, "rs6054257", sm, "rs6040355", sm, "microsat1", sm, "rsTest"],
     )
     assert ds["variant_id"].chunks[0][0] == 5
-    assert ds["variant_id"].dtype == "O"
+    assert ds["variant_id"].dtype.kind in ("O", "T")
     assert_array_equal(
         ds["variant_id_mask"],
         [True, True, False, True, False, True, False, True, False],
@@ -246,4 +247,11 @@ def test_vcf2zarr_compat(shared_datadir, tmp_path):
     # save and load again to test https://github.com/pydata/xarray/issues/3476
     path2 = tmp_path / "ds2.zarr"
     save_dataset(ds, path2)
-    assert_identical(ds, load_dataset(path2))
+    ds2 = load_dataset(path2)
+    xr.testing.assert_identical(ds, ds2)
+    for name in ds:
+        if ds[name].dtype.kind == "T":
+            # Recent Xarray writes NumPy StringDType as fixed-width Unicode.
+            assert ds2[name].dtype.kind in ("T", "U")
+        else:
+            assert ds[name].dtype == ds2[name].dtype
diff --git a/sgkit/tests/test_association.py b/sgkit/tests/test_association.py
index aad1bef19..4ccc8f4d9 100644
--- a/sgkit/tests/test_association.py
+++ b/sgkit/tests/test_association.py
@@ -8,11 +8,7 @@
 import xarray as xr
 from pandas import DataFrame
 from xarray import Dataset
-
-try:
-    from zarr.storage import ZipStore  # v3
-except ImportError:  # pragma: no cover
-    from zarr import ZipStore
+from zarr.storage import ZipStore
 
 import sgkit.distarray as da
 from sgkit.stats.association import (
diff --git a/sgkit/tests/test_regenie.py b/sgkit/tests/test_regenie.py
index 76ad69abb..8b1c650ef 100644
--- a/sgkit/tests/test_regenie.py
+++ b/sgkit/tests/test_regenie.py
@@ -16,11 +16,7 @@
 from hypothesis.strategies import data as st_data
 from pandas import DataFrame
 from xarray import Dataset
-
-try:
-    from zarr.storage import ZipStore  # v3
-except ImportError:  # pragma: no cover
-    from zarr import ZipStore
+from zarr.storage import ZipStore
 
 from sgkit.stats.association import LinearRegressionResult, linear_regression
 from sgkit.stats.regenie import (
diff --git a/sgkit/utils.py b/sgkit/utils.py
index f60db1f91..ee9bbfd3f 100644
--- a/sgkit/utils.py
+++ b/sgkit/utils.py
@@ -1,4 +1,3 @@
-import inspect
 import warnings
 from itertools import product
 from typing import Any, Callable, Hashable, List, Mapping, Optional, Set, Tuple, Union
@@ -426,10 +425,3 @@ def smallest_numpy_int_dtype(value: int) -> Optional[DType]:
         if np.iinfo(dtype).min <= value <= np.iinfo(dtype).max:
             return dtype
     raise OverflowError(f"Value {value} cannot be stored in np.int64")
-
-
-def has_keyword(func, keyword):
-    try:
-        return keyword in inspect.signature(func).parameters
-    except Exception:  # pragma: no cover
-        return False
diff --git a/uv.lock b/uv.lock
index 170bddde4..cadff5fda 100644
--- a/uv.lock
+++ b/uv.lock
@@ -209,12 +209,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/46/c7/6b687cb0f83d2a51017d47953f2ee430ffad6fec2a8ebc964e0718a33eb1/appnope-1.0.0-py3-none-any.whl", hash = "sha256:6fe0c04218aab65c54c4ff81638cdbf848d89f5653b74d68638a137f200dd16e", size = 4158, upload-time = "2026-08-20T21:36:12.444Z" },
 ]
 
-[[package]]
-name = "asciitree"
-version = "0.3.3"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/2d/6a/885bc91484e1aa8f618f6f0228d76d0e67000b0fdd6090673b777e311913/asciitree-0.3.3.tar.gz", hash = "sha256:4aa4b9b649f85e3fcb343363d97564aa1fb62e249677f2e18a96765145cc0f6e", size = 3951, upload-time = "2016-09-05T19:10:42.681Z" }
-
 [[package]]
 name = "asttokens"
 version = "3.0.2"
@@ -297,22 +291,22 @@ wheels = [
 
 [[package]]
 name = "bio2zarr"
-version = "0.1.7"
+version = "0.2.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "click" },
     { name = "coloredlogs" },
     { name = "humanfriendly" },
-    { name = "numcodecs", extra = ["msgpack"] },
     { name = "numpy" },
     { name = "pandas" },
     { name = "tabulate" },
     { name = "tqdm" },
-    { name = "zarr" },
+    { name = "zarr", version = "3.1.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "zarr", version = "3.4.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/8d/8f/9f79bfdde3dc98228dc0030bad8f668199c811111f5842bd3b3ff5c752d3/bio2zarr-0.1.7.tar.gz", hash = "sha256:237aa8af904bb29172a0cb8a525527d0ad8e5a855d214d8a5be29b39b4334b2c", size = 262655, upload-time = "2026-02-03T15:44:52.011Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/82/98/96c14b30e96c581362513ea29520efdf6cfa2b9f222deb0a87377ab2be33/bio2zarr-0.2.1.tar.gz", hash = "sha256:5bbab214c7b12ec99459e9e08a7575f21bc5415b31d6385cf80a7ff55e097b63", size = 405736, upload-time = "2026-06-04T11:20:04.196Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/9c/34/b827ccb81a4ed1a4e90cd968dfa94efc339b9e32dc354602a302d199a935/bio2zarr-0.1.7-py3-none-any.whl", hash = "sha256:95eabaada6a2fae02c4c2ea52fb7e4684de3b45bc3b521a13855353a8e50d1c6", size = 61768, upload-time = "2026-02-03T15:44:50.564Z" },
+    { url = "https://files.pythonhosted.org/packages/11/2e/d69c09b3727630169361827a9cd7ef10aae7a9edfc91ae01c8ba6f474e51/bio2zarr-0.2.1-py3-none-any.whl", hash = "sha256:989d993fef83d64a8eff54770625601a4a4108f86149fc7a7bfbbd6b6e2af010", size = 63715, upload-time = "2026-06-04T11:20:02.904Z" },
 ]
 
 [package.optional-dependencies]
@@ -320,57 +314,6 @@ vcf = [
     { name = "cyvcf2" },
 ]
 
-[[package]]
-name = "bokeh"
-version = "3.9.2"
-source = { registry = "https://pypi.org/simple" }
-resolution-markers = [
-    "python_full_version < '3.12' and sys_platform == 'darwin'",
-    "python_full_version < '3.12' and sys_platform != 'darwin'",
-]
-dependencies = [
-    { name = "contourpy" },
-    { name = "jinja2" },
-    { name = "narwhals" },
-    { name = "numpy" },
-    { name = "packaging" },
-    { name = "pillow" },
-    { name = "pyyaml" },
-    { name = "tornado", marker = "sys_platform != 'emscripten'" },
-    { name = "xyzservices" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/dd/6f/262b649ad2fdd5ed23341452eebfa669a73b0e0c739a369204d02ee2e201/bokeh-3.9.2.tar.gz", hash = "sha256:5be30d105b329d7d2ab1cb92f51e6bd44e23f0fe21ab8d49594b220b2ab11632", size = 5751825, upload-time = "2026-07-25T16:57:56.207Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/ca/0c/06a99ee998b1babf95074376cbf6ede5a86af726b12cbf47c4b84fa2803a/bokeh-3.9.2-py3-none-any.whl", hash = "sha256:448e07d5ee78231f5bdece3be020024bb98696c0d6b127e0e2df0b8ba8fa9765", size = 6409477, upload-time = "2026-07-25T16:57:54.62Z" },
-]
-
-[[package]]
-name = "bokeh"
-version = "3.10.0"
-source = { registry = "https://pypi.org/simple" }
-resolution-markers = [
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-    "python_full_version >= '3.14' and sys_platform != 'darwin'",
-    "python_full_version == '3.13.*' and sys_platform == 'darwin'",
-    "python_full_version == '3.13.*' and sys_platform != 'darwin'",
-    "python_full_version == '3.12.*' and sys_platform == 'darwin'",
-    "python_full_version == '3.12.*' and sys_platform != 'darwin'",
-]
-dependencies = [
-    { name = "jinja2" },
-    { name = "narwhals" },
-    { name = "numpy" },
-    { name = "packaging" },
-    { name = "pillow" },
-    { name = "pyyaml" },
-    { name = "tornado", marker = "sys_platform != 'emscripten'" },
-    { name = "xyzservices" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/4c/e8/93d270023eb987348f9b5a2aef0103f903511b934519cd2bbefde451868d/bokeh-3.10.0.tar.gz", hash = "sha256:73f0b0c06d7925ca2b6d52b2dc51c2533a11f667cc6944f1f06c039ccc57c5ce", size = 5982193, upload-time = "2026-08-18T17:47:09.943Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/c5/0a/1423bb61b5f06376fe6ccf79c8781e2bb5e36c78c1814c78913b7425950f/bokeh-3.10.0-py3-none-any.whl", hash = "sha256:6bb8dbd4a555f71a921be5bd45c3bfaa15b390257fbadae76901927bd58629b7", size = 6649702, upload-time = "2026-08-18T17:47:07.287Z" },
-]
-
 [[package]]
 name = "callee"
 version = "0.3.1"
@@ -1036,11 +979,6 @@ dataframe = [
     { name = "numpy" },
     { name = "pandas" },
 ]
-diagnostics = [
-    { name = "bokeh", version = "3.9.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
-    { name = "bokeh", version = "3.10.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
-    { name = "jinja2" },
-]
 
 [[package]]
 name = "dask-expr"
@@ -1125,21 +1063,24 @@ wheels = [
 ]
 
 [[package]]
-name = "executing"
-version = "2.2.1"
+name = "donfig"
+version = "0.8.1.post1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/cc/28/c14e053b6762b1044f34a13aab6859bbf40456d37d23aa286ac24cfd9a5d/executing-2.2.1.tar.gz", hash = "sha256:3632cc370565f6648cc328b32435bd120a1e4ebb20c77e3fdde9a13cd1e533c4", size = 1129488, upload-time = "2025-09-01T09:48:10.866Z" }
+dependencies = [
+    { name = "pyyaml" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/25/71/80cc718ff6d7abfbabacb1f57aaa42e9c1552bfdd01e64ddd704e4a03638/donfig-0.8.1.post1.tar.gz", hash = "sha256:3bef3413a4c1c601b585e8d297256d0c1470ea012afa6e8461dc28bfb7c23f52", size = 19506, upload-time = "2024-05-23T14:14:31.513Z" }
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+    { url = "https://files.pythonhosted.org/packages/0c/d5/c5db1ea3394c6e1732fb3286b3bd878b59507a8f77d32a2cebda7d7b7cd4/donfig-0.8.1.post1-py3-none-any.whl", hash = "sha256:2a3175ce74a06109ff9307d90a230f81215cbac9a751f4d1c6194644b8204f9d", size = 21592, upload-time = "2024-05-23T14:13:55.283Z" },
 ]
 
 [[package]]
-name = "fasteners"
-version = "0.20"
+name = "executing"
+version = "2.2.1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/2d/18/7881a99ba5244bfc82f06017316ffe93217dbbbcfa52b887caa1d4f2a6d3/fasteners-0.20.tar.gz", hash = "sha256:55dce8792a41b56f727ba6e123fcaee77fd87e638a6863cec00007bfea84c8d8", size = 25087, upload-time = "2025-08-11T10:19:37.785Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/cc/28/c14e053b6762b1044f34a13aab6859bbf40456d37d23aa286ac24cfd9a5d/executing-2.2.1.tar.gz", hash = "sha256:3632cc370565f6648cc328b32435bd120a1e4ebb20c77e3fdde9a13cd1e533c4", size = 1129488, upload-time = "2025-09-01T09:48:10.866Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl", hash = "sha256:760643d3452b4d777d295bb167ccc74c64a81df23fb5e08eff250c425a4b2017", size = 28317, upload-time = "2025-09-01T09:48:08.5Z" },
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 [[package]]
@@ -1367,6 +1308,39 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fd/3c/6a2bf344106328fd04963664a60b9bb6496fc25df8e962fcdc1367285fb9/fsspec-2026.7.0-py3-none-any.whl", hash = "sha256:b57ddbafedfaef7018c1ecab32aa200a9d7ca26b77965f64e48b70061249d279", size = 206583, upload-time = "2026-07-28T16:34:49.538Z" },
 ]
 
+[[package]]
+name = "google-crc32c"
+version = "1.9.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/fa/25/9cb0c1c31c45b893eb8f11ae70b3f4309432d59b5acaebca5dbe791729a4/google_crc32c-1.9.0.tar.gz", hash = "sha256:7b8c84c3d159ab6817fe3f74e6e6cef099c3f95dcec3abc0d8afb1404642efbe", size = 14857, upload-time = "2026-09-24T21:39:32.067Z" }
+wheels = [
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@@ -4116,7 +4119,7 @@ provides-extras = ["plink", "bgen"]
 dev = [
     { name = "ablog", specifier = "!=0.10.27" },
     { name = "aiohttp" },
-    { name = "bio2zarr", extras = ["vcf"], marker = "sys_platform != 'win32'" },
+    { name = "bio2zarr", extras = ["vcf"], marker = "sys_platform != 'win32'", specifier = ">=0.2" },
     { name = "callee" },
     { name = "graphviz" },
     { name = "hypothesis" },
@@ -4163,7 +4166,7 @@ lint = [{ name = "pre-commit" }]
 packaging = [{ name = "twine" }]
 test = [
     { name = "aiohttp" },
-    { name = "bio2zarr", extras = ["vcf"], marker = "sys_platform != 'win32'" },
+    { name = "bio2zarr", extras = ["vcf"], marker = "sys_platform != 'win32'", specifier = ">=0.2" },
     { name = "callee" },
     { name = "graphviz" },
     { name = "hypothesis" },
@@ -4785,25 +4788,16 @@ wheels = [
 
 [[package]]
 name = "xarray"
-version = "2025.3.0"
+version = "2026.9.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "numpy" },
     { name = "packaging" },
     { name = "pandas" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/8a/8c/e56820a2c682834d8fb4a940956cd41b9f2532fee9692bfaf43b14f33c6e/xarray-2025.3.0.tar.gz", hash = "sha256:531cf6d64e6ab54c19239930a840654f1a79d2140e9f0d11d1e8d69dcc581d0f", size = 3292399, upload-time = "2025-03-20T04:50:58.903Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/ff/f5/781c70b234f54e0401f4f7c4427a7486da38d50dbb138c7d7c55144b3d86/xarray-2026.9.0.tar.gz", hash = "sha256:6abc69694c22fa1f0fb2f357ff4e41d88beb4477ed71091f944b7dbf67ed54fe", size = 3176922, upload-time = "2026-09-29T23:06:25.807Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/91/19/5dbac77ca82f009f8267d0e7cca4fd3be2a435d83ed98f6f8b9c5cb1747e/xarray-2025.3.0-py3-none-any.whl", hash = "sha256:022b7eac5ebc26d70d34211de732ec1a15127a40455f9492acdde7fbe5bbf091", size = 1270849, upload-time = "2025-03-20T04:50:56.457Z" },
-]
-
-[[package]]
-name = "xyzservices"
-version = "2026.9.1"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/c4/bd/b75d5c2312caec607ec995200fa1eb8453225fd869947ec743919c279544/xyzservices-2026.9.1.tar.gz", hash = "sha256:8d1a39bf6b192940cc5db5264eeefc1b20dd184f8b83b1303b078743744f5943", size = 1134047, upload-time = "2026-09-04T10:35:41.399Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/a8/71/9219fe65ef32bddc0b5d14e1d98dfefe9d2c9c1b1d1e93efca1f29fcbd4d/xyzservices-2026.9.1-py3-none-any.whl", hash = "sha256:af4fddac0f1fa5f7951834e2c58e10109e722be548cb1fe4f1a8e8b18cef4c09", size = 98829, upload-time = "2026-09-04T10:35:40.08Z" },
+    { url = "https://files.pythonhosted.org/packages/3f/44/3159af4fb3c868970a412e294320ed6bb1a9fbdfa6431050eda8e0b34b6e/xarray-2026.9.0-py3-none-any.whl", hash = "sha256:fe349fa871628b1a0a5217af3fe1283a2862d5485156e6eda354fffb81c3bb7c", size = 1445445, upload-time = "2026-09-29T23:06:23.686Z" },
 ]
 
 [[package]]
@@ -4907,17 +4901,49 @@ wheels = [
 
 [[package]]
 name = "zarr"
-version = "2.18.7"
+version = "3.1.6"
 source = { registry = "https://pypi.org/simple" }
+resolution-markers = [
+    "python_full_version < '3.12' and sys_platform == 'darwin'",
+    "python_full_version < '3.12' and sys_platform != 'darwin'",
+]
 dependencies = [
-    { name = "asciitree" },
-    { name = "fasteners", marker = "sys_platform != 'emscripten'" },
-    { name = "numcodecs" },
+    { name = "donfig" },
+    { name = "google-crc32c" },
+    { name = "numcodecs", version = "0.15.1", source = { registry = "https://pypi.org/simple" } },
     { name = "numpy" },
+    { name = "packaging" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/31/5a/b8a0cf39a14c770c30bd1f2d120c54000c8cd9e84e8e79f38d9a7ce58071/zarr-3.1.6.tar.gz", hash = "sha256:d95e72cbea4b90e9a70679468b8266400331756232576ae2b43400ac5108d0eb", size = 386531, upload-time = "2026-03-23T17:25:18.748Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/de/7c/ba8ca8cbe9dbef8e83a95fc208fed8e6686c98b4719aaa0aa7f3d31fe390/zarr-3.1.6-py3-none-any.whl", hash = "sha256:b5a82c5079d1c3d4ee8f06746fa3b9a98a7d804300fa3f4be154362a33e1207e", size = 295655, upload-time = "2026-03-23T17:25:17.189Z" },
+]
+
+[[package]]
+name = "zarr"
+version = "3.4.1"
+source = { registry = "https://pypi.org/simple" }
+resolution-markers = [
+    "python_full_version >= '3.14' and sys_platform == 'darwin'",
+    "python_full_version >= '3.14' and sys_platform != 'darwin'",
+    "python_full_version == '3.13.*' and sys_platform == 'darwin'",
+    "python_full_version == '3.13.*' and sys_platform != 'darwin'",
+    "python_full_version == '3.12.*' and sys_platform == 'darwin'",
+    "python_full_version == '3.12.*' and sys_platform != 'darwin'",
+]
+dependencies = [
+    { name = "donfig" },
+    { name = "google-crc32c" },
+    { name = "msgspec" },
+    { name = "numcodecs", version = "0.17.0", source = { registry = "https://pypi.org/simple" } },
+    { name = "numpy" },
+    { name = "packaging" },
+    { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/da/1d/01cf9e3ab2d85190278efc3fca9f68563de35ae30ee59e7640e3af98abe3/zarr-2.18.7.tar.gz", hash = "sha256:b2b8f66f14dac4af66b180d2338819981b981f70e196c9a66e6bfaa9e59572f5", size = 3604558, upload-time = "2025-04-09T07:59:28.482Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/3e/62/e8a36a4b65f01499c7aefcf103aabba0c37c018bf135fbf179f6ed2f01a0/zarr-3.4.1.tar.gz", hash = "sha256:b34bda11ceb199c81ee78ecd42cd02f46c7f67a6d8a1e9bc501cafd5a1795356", size = 923257, upload-time = "2026-10-08T17:14:25.972Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/5e/d8/9ffd8c237b3559945bb52103cf0eed64ea098f7b7f573f8d2962ef27b4b2/zarr-2.18.7-py3-none-any.whl", hash = "sha256:ac3dc4033e9ae4e9d7b5e27c97ea3eaf1003cc0a07f010bd83d5134bf8c4b223", size = 211273, upload-time = "2025-04-09T07:59:27.039Z" },
+    { url = "https://files.pythonhosted.org/packages/a6/82/0dbc9bc77b49cfb9268dc2b2b1dcd04346c8c7ed52e272b76a628a941656/zarr-3.4.1-py3-none-any.whl", hash = "sha256:38b540578a119352bdce02a720d7bfd99846e77f0728c58b1bab3d1f547526a0", size = 405257, upload-time = "2026-10-08T17:14:23.926Z" },
 ]
 
 [[package]]

From e18e9f5ab96b29375999e7858c81923ad8bd9344 Mon Sep 17 00:00:00 2001
From: Julianus Pfeuffer <8102638+jpfeuffer@users.noreply.github.com>
Date: Fri, 16 Oct 2026 10:00:12 +0200
Subject: [PATCH 2/7] Remove legacy BGEN conversion and document bio2zarr
 migration

Drop bgen_to_zarr and rechunk_bgen following the maintainer decision. Preserve direct BGEN reading and legacy store unpacking, with tested manual read/chunk/save instructions while bio2zarr BGEN support is pending. Prominently document conversion via bio2zarr in the README, changelog, user guide and API reference.

Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
---
 README.md                               |   7 +
 docs/api.rst                            |  10 +-
 docs/changelog.rst                      |  17 +-
 docs/conf.py                            |   6 +-
 docs/user_guide.rst                     |  66 ++++--
 sgkit/io/bgen/__init__.py               |   4 +-
 sgkit/io/bgen/bgen_reader.py            | 261 +-----------------------
 sgkit/tests/io/bgen/test_bgen_reader.py | 152 ++++----------
 8 files changed, 123 insertions(+), 400 deletions(-)

diff --git a/README.md b/README.md
index d27828743..629a68c5f 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,13 @@ general-purpose frameworks such as [Xarray](http://xarray.pydata.org/en/stable/)
 
 For more information on using sgkit, see the [documentation](https://sgkit-dev.github.io/sgkit/).
 
+**Genetic file conversion:** Use [bio2zarr](https://sgkit-dev.github.io/bio2zarr/)
+to convert genetic file formats to Zarr, then load them with `sgkit.load_dataset`.
+The deprecated `bgen_to_zarr` and `rechunk_bgen` functions have been removed.
+Bio2zarr's BGEN support is [still pending](https://github.com/sgkit-dev/bio2zarr/issues/417);
+see the [BGEN migration guide](docs/user_guide.rst#bgen) for the interim
+`read_bgen` / Xarray `chunk` / `save_dataset` workflow.
+
 [//]: # (numfocus-fiscal-sponsor-attribution)
 
 The sgkit project uses a [custom governance model](./GOVERNANCE.md) 
diff --git a/docs/api.rst b/docs/api.rst
index 512a3ccda..b7fc6e59b 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -9,6 +9,14 @@ IO/imports and exports
 
 See :ref:`reading_and_writing_genetic_data`
 
+.. important::
+
+   **Use bio2zarr for genetic file format conversion to Zarr**, then load the
+   converted dataset with :func:`sgkit.load_dataset`. The deprecated BGEN
+   conversion functions ``bgen_to_zarr`` and ``rechunk_bgen`` have been removed.
+   BGEN support in bio2zarr is still pending; see :ref:`bgen_conversion_migration`
+   for the interim read/chunk/save workflow.
+
 BGEN
 -----
 
@@ -16,9 +24,7 @@ BGEN
 .. autosummary::
    :toctree: generated/
 
-   bgen_to_zarr
    read_bgen
-   rechunk_bgen
 
 PLINK
 -----
diff --git a/docs/changelog.rst b/docs/changelog.rst
index b2f98dfb3..5886f27ba 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -16,9 +16,16 @@ Breaking changes
 
 - Require Zarr Python >= 3 and Xarray >= 2026.9.0. The default on-disk Zarr
   format remains 2. (:issue:`1355`)
-- Remove the incompatible rechunker dependency from the BGEN extra. The
-  deprecated BGEN conversion functions now use Xarray and Dask; ``max_mem``
-  and ``tempdir`` no longer control rechunking.
+- **Remove the deprecated BGEN conversion functions** ``sgkit.io.bgen.bgen_to_zarr``
+  and ``sgkit.io.bgen.rechunk_bgen``, along with their rechunker dependency.
+  **Use bio2zarr for genetic file format conversion to Zarr**, and load the
+  result with :func:`load_dataset`. BGEN support in bio2zarr is still pending
+  (`bio2zarr issue 417 <https://github.com/sgkit-dev/bio2zarr/issues/417>`_).
+  Until then, BGEN users can call :func:`sgkit.io.bgen.read_bgen`,
+  :meth:`xarray.Dataset.chunk`, and :func:`save_dataset` explicitly; this does
+  not reproduce the old probability quantization, packing, or ``max_mem``/
+  ``tempdir`` controls. See :ref:`bgen_conversion_migration`.
+  (:pr:`1325`, :issue:`1355`)
 
 Deprecations
 ~~~~~~~~~~~~
@@ -26,10 +33,6 @@ Deprecations
 - Functions for reading and writing plink are deprecated, please use the `bio2zarr <https://github.com/sgkit-dev/bio2zarr>`_
   and `vcztools <https://github.com/sgkit-dev/vcztools>`_ packages.
   (:user:`tomwhite`, :pr:`1324`, :issue:`1318`)
-- Using rechunker for rechunking in sgkit is deprecated, please use the the
-  `Xarray chunk <https://docs.xarray.dev/en/stable/generated/xarray.Dataset.chunk.html#xarray.Dataset.chunk>`_
-  function directly.
-  (:user:`tomwhite`, :pr:`1325`)
 
 .. Improvements
 .. ~~~~~~~~~~~~
diff --git a/docs/conf.py b/docs/conf.py
index a71360b68..482d17157 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -117,7 +117,11 @@ def filter(self, record: pylogging.LogRecord) -> bool:
 
 autosummary_generate = True
 
-nitpick_ignore = [("py:class", "sgkit.display.GenotypeDisplay")]
+nitpick_ignore = [
+    ("py:class", "sgkit.display.GenotypeDisplay"),
+    # Zarr's StoreLike alias is rendered as an undocumented TypeAliasType.
+    ("py:class", "zarr.storage._common.TypeAliasType"),
+]
 
 
 # FIXME: Workaround for linking xarray module
diff --git a/docs/user_guide.rst b/docs/user_guide.rst
index 76cacca96..942b9ad53 100644
--- a/docs/user_guide.rst
+++ b/docs/user_guide.rst
@@ -13,6 +13,17 @@ User Guide
 Reading and writing genetic data
 ================================
 
+.. important::
+
+   **Use bio2zarr for genetic file format conversion to Zarr**, then use
+   :func:`sgkit.load_dataset` for analysis in sgkit. See the
+   `bio2zarr documentation <https://sgkit-dev.github.io/bio2zarr/>`_ for
+   installation and conversion instructions.
+
+   The deprecated BGEN conversion functions ``bgen_to_zarr`` and ``rechunk_bgen``
+   have been removed. BGEN conversion in bio2zarr is still pending; BGEN users
+   should follow :ref:`bgen_conversion_migration` in the meantime.
+
 .. _installation:
 
 Installation
@@ -38,18 +49,12 @@ To install sgkit with PLINK support::
 Converting genetic data to Zarr
 -------------------------------
 
-There are broadly two ways of loading genetic file format ``X`` for use in sgkit:
-
-1. a ``read_X`` function to read the file directly
-2. a ``X_to_zarr`` function to convert to Zarr first
-
-Which one to use depends on the size of the input, as well as the file format (not all file
-formats have both options).
-
-Generally speaking, the ``read_X`` functions are convenience functions that are suitable
-for small input files, or where the cost of conversion is small. The ``X_to_zarr`` functions
-are more appropriate for large datasets, since the expensive conversion step need only be
-paid once.
+Genetic file format conversion belongs in
+`bio2zarr <https://sgkit-dev.github.io/bio2zarr/>`__, rather than sgkit.
+Convert VCF and PLINK inputs with bio2zarr before analysis, so the expensive
+conversion step need only be paid once. The direct ``read_X`` functions are
+convenience functions for small inputs or cases where the cost of reading is small;
+the PLINK functions are deprecated.
 
 After converting a file to Zarr format, it can be loaded with sgkit's :func:`sgkit.load_dataset`.
 This is like Xarray's :func:`xarray.open_zarr` function, with some useful defaults applied for you.
@@ -69,25 +74,46 @@ by recent Zarr releases, preserving string-array chunking on load.
 By default, Zarr format 2 datasets created by sgkit have `consolidated metadata <http://xarray.pydata.org/en/stable/user-guide/io.html#consolidated-metadata>`_,
 which makes opening the dataset faster.
 
+.. _bgen_conversion_migration:
+
 BGEN
 ----
 
 The :func:`sgkit.io.bgen.read_bgen` function loads a single BGEN dataset as Dask
 arrays within an :class:`xarray.Dataset` from a ``bgen`` file.
 
-The :func:`sgkit.io.bgen.bgen_to_zarr` function converts a ``bgen`` file to Zarr
-files stored in sgkit's Xarray data representation, which can then be opened
-as a :class:`xarray.Dataset`.
+.. warning::
 
-The deprecated BGEN conversion functions now rechunk with Xarray and Dask,
-without the Zarr Python 2-only rechunker package. They still write Zarr format 2
-and preserve probability encoding and packing. The ``max_mem`` and ``tempdir``
-parameters are retained for compatibility but no longer have an effect; configure
-chunk sizes and the Dask scheduler to control memory use.
+   ``sgkit.io.bgen.bgen_to_zarr`` and ``sgkit.io.bgen.rechunk_bgen`` have been
+   removed. New format-conversion workflows should use bio2zarr, but
+   **bio2zarr does not yet support BGEN input**. Progress is tracked in
+   `bio2zarr issue 417 <https://github.com/sgkit-dev/bio2zarr/issues/417>`_.
+
+Until BGEN support is available in bio2zarr, the equivalent read/chunk/save
+steps can be performed explicitly::
+
+    import sgkit as sg
+    from sgkit.io.bgen import read_bgen
+
+    ds = read_bgen("input.bgen")
+    ds = ds.chunk({"variants": 10000, "samples": 1000})
+    sg.save_dataset(ds, "output.zarr")
+
+Choose chunk sizes and Dask scheduler settings appropriate to the available
+memory. This example retains the reader's floating-point genotype probabilities
+and dosages; it does not perform the removed converters' lossy integer
+quantization or variable packing. There are no ``max_mem`` or ``tempdir``
+arguments; those belonged to the removed rechunker-based conversion API.
+The ``unpack_variables`` helper in ``sgkit.io.bgen.bgen_reader`` remains
+available to restore probabilities and dosages from existing packed stores.
 
 PLINK
 -----
 
+Use `bio2zarr <https://sgkit-dev.github.io/bio2zarr/>`__ for PLINK-to-Zarr
+conversion and `vcztools <https://github.com/sgkit-dev/vcztools>`_ for export.
+The following sgkit PLINK functions are deprecated.
+
 The :func:`sgkit.io.plink.read_plink` function loads a single PLINK dataset as Dask
 arrays within an :class:`xarray.Dataset` from ``bed``, ``bim``, and ``fam`` files.
 
diff --git a/sgkit/io/bgen/__init__.py b/sgkit/io/bgen/__init__.py
index 8d57ccd82..f45ee4ac7 100644
--- a/sgkit/io/bgen/__init__.py
+++ b/sgkit/io/bgen/__init__.py
@@ -1,7 +1,7 @@
 try:
-    from .bgen_reader import bgen_to_zarr, read_bgen, rechunk_bgen
+    from .bgen_reader import read_bgen
 
-    __all__ = ["read_bgen", "bgen_to_zarr", "rechunk_bgen"]
+    __all__ = ["read_bgen"]
 except ImportError as e:  # pragma: no cover
     msg = (
         "sgkit bgen requirements are not installed.\n\n"
diff --git a/sgkit/io/bgen/bgen_reader.py b/sgkit/io/bgen/bgen_reader.py
index e9212d229..46142b847 100644
--- a/sgkit/io/bgen/bgen_reader.py
+++ b/sgkit/io/bgen/bgen_reader.py
@@ -1,34 +1,24 @@
 """BGEN reader implementation (using bgen_reader)"""
 import logging
 import time
-import warnings
 from pathlib import Path
-from typing import Any, Dict, Hashable, List, Mapping, Optional, Tuple, Union
+from typing import Any, List, Optional, Tuple, Union
 
 import dask
 import dask.array as da
 import dask.dataframe as dd
-import numcodecs
 import numpy as np
 import pandas as pd
 import xarray as xr
 from cbgen import bgen_file, bgen_metafile
 from xarray import Dataset
-from zarr.storage import StoreLike
 
-from sgkit import create_genotype_dosage_dataset, variables
+from sgkit import create_genotype_dosage_dataset
 from sgkit.io.utils import dataframe_to_dict, encode_contigs
 from sgkit.typing import ArrayLike, DType, NDArray, PathType
 
 logger = logging.getLogger(__name__)
 
-GT_DATA_VARS = [
-    variables.call_genotype_probability,
-    variables.call_genotype_probability_mask,
-    variables.call_dosage,
-    variables.call_dosage_mask,
-]
-
 METAFILE_DTYPE = dict(
     [
         ("id", "S"),
@@ -329,62 +319,8 @@ def _to_dosage(probs: ArrayLike) -> ArrayLike:
     return probs[..., 1] + 2 * probs[..., 2]
 
 
-########################
-# Rechunking Functions #
-########################
-
-
-def encode_variables(
-    ds: Dataset,
-    chunk_length: int,
-    chunk_width: int,
-    compressor: Optional[Any] = numcodecs.Blosc(cname="zstd", clevel=7, shuffle=2),
-    probability_dtype: Optional[Any] = "uint8",
-) -> Dict[Hashable, Dict[str, Any]]:
-    encoding = {}
-    for v in ds:
-        e = {"compressors": compressor}
-        if v in GT_DATA_VARS:
-            e.update({"chunks": (chunk_length, chunk_width) + ds[v].shape[2:]})
-        if probability_dtype is not None and v == "call_genotype_probability":
-            dtype = np.dtype(probability_dtype)
-            # Xarray will decode into float32 so any int greater than
-            # 16 bits will cause overflow/underflow
-            # See https://en.wikipedia.org/wiki/Floating-point_arithmetic#Internal_representation
-            # *bits precision column for single precision floats
-            if dtype not in [np.uint8, np.uint16]:  # type: ignore[comparison-overlap]
-                raise ValueError(
-                    "Probability integer dtype invalid, must "
-                    f"be uint8 or uint16 not {probability_dtype}"
-                )
-            divisor = np.iinfo(dtype).max - 1
-            e.update(
-                {
-                    "dtype": probability_dtype,
-                    "add_offset": -1.0 / divisor,
-                    "scale_factor": 1.0 / divisor,
-                    "_FillValue": 0,
-                }
-            )
-        if e:
-            encoding[v] = e
-    return encoding
-
-
-def pack_variables(ds: Dataset) -> Dataset:
-    # Remove dosage as it is unnecessary and should be redefined
-    # based on encoded probabilities later (w/ reduced precision)
-    ds = ds.drop_vars(["call_dosage", "call_dosage_mask"], errors="ignore")
-
-    # Remove homozygous reference GP and redefine mask
-    gp = ds["call_genotype_probability"][..., 1:]
-    gp_mask = ds["call_genotype_probability_mask"].any(dim="genotypes")
-    ds = ds.drop_vars(["call_genotype_probability", "call_genotype_probability_mask"])
-    ds = ds.assign(call_genotype_probability=gp, call_genotype_probability_mask=gp_mask)
-    return ds
-
-
 def unpack_variables(ds: Dataset, dtype: DType = "float32") -> Dataset:
+    """Restore probabilities and dosages from legacy packed BGEN-derived stores."""
     # Restore homozygous reference GP
     gp = ds["call_genotype_probability"].astype(dtype)
     if gp.sizes["genotypes"] != 2:
@@ -404,194 +340,3 @@ def unpack_variables(ds: Dataset, dtype: DType = "float32") -> Dataset:
         "call_genotype_probability_mask"
     ].broadcast_like(ds["call_genotype_probability"])
     return ds
-
-
-def rechunk_bgen(
-    ds: Dataset,
-    output: StoreLike,
-    *,
-    chunk_length: int = 10_000,
-    chunk_width: int = 1_000,
-    compressor: Optional[Any] = numcodecs.Blosc(cname="zstd", clevel=7, shuffle=2),
-    probability_dtype: Optional[DType] = "uint8",
-    max_mem: str = "4GB",
-    pack: bool = True,
-    tempdir: Optional[PathType] = None,
-) -> Dataset:
-    """Rechunk BGEN dataset as Zarr.
-
-    This function uses Xarray and Dask to rechunk a Dataset for better downstream
-    performance and writes Zarr format 2. It no longer uses rechunker, which does
-    not support Zarr Python 3. Memory usage depends on the input and output chunks
-    and the Dask scheduler; no intermediate store is created.
-    Experiments show that this Zarr representation is ~20% larger even
-    with all available optimizations and fairly aggressive compression (i.e. the
-    default `clevel` 7).
-
-    Note that this function is not evaluated lazily. The rechunking algorithm
-    will run inline so calls to it may be slow. The resulting Dataset is
-    generated based on the final, serialized Zarr data.
-
-    .. deprecated:: 0.11.0
-       This conversion helper is deprecated, please use the
-       `Xarray chunk <https://docs.xarray.dev/en/stable/generated/xarray.Dataset.chunk.html#xarray.Dataset.chunk>`_
-       function directly.
-
-    Parameters
-    ----------
-    ds
-        Dataset to rechunk, typically the result from `read_bgen`.
-    output
-        Zarr store or path to directory in file system.
-    chunk_length
-        Length (number of variants) of chunks in which data are stored, by default 10_000.
-    chunk_width
-        Width (number of samples) to use when storing chunks in output, by default 1_000.
-    compressor
-        Zarr compressor, no compression is used when set as None.
-    probability_dtype
-        Data type used to encode genotype probabilities, must be either uint8 or uint16.
-        Setting this parameter results in a loss of precision. If None, probabilities
-        will not be altered when stored.
-    max_mem
-        Deprecated and no longer used. Memory is managed by Dask.
-    pack
-        Whether or not to optimize variable representations by removing unnecessary
-        dimensions and elements. This includes storing 2 genotypes instead of 3, omitting
-        dosage and collapsing the genotype probability mask to 2 dimensions. All of
-        the above are restored in the resulting Dataset at the expense of extra
-        computations on read.
-    tempdir
-        Deprecated and no longer used. No intermediate store is created.
-
-    Warnings
-    --------
-
-    This functional is only applicable to diploid, bi-allelic BGEN datasets.
-
-    Returns
-    -------
-
-    Dataset
-        The rechunked dataset.
-    """
-    warnings.warn(
-        "rechunk_bgen is deprecated, please use Xarray 'chunk' and sgkit.save_dataset directly.",
-        DeprecationWarning,
-        stacklevel=2,
-    )
-    if max_mem != "4GB" or tempdir is not None:
-        warnings.warn(
-            "max_mem and tempdir no longer control BGEN rechunking; "
-            "memory is managed by Dask and no intermediate store is created.",
-            FutureWarning,
-            stacklevel=2,
-        )
-
-    if isinstance(output, Path):
-        output = str(output)
-
-    chunk_length = min(chunk_length, ds.sizes["variants"])
-    chunk_width = min(chunk_width, ds.sizes["samples"])
-
-    if pack:
-        ds = pack_variables(ds)
-
-    encoding = encode_variables(
-        ds,
-        chunk_length=chunk_length,
-        chunk_width=chunk_width,
-        compressor=compressor,
-        probability_dtype=probability_dtype,
-    )
-    ds = ds.chunk({"variants": chunk_length, "samples": chunk_width})
-    ds.to_zarr(output, encoding=encoding, zarr_format=2, consolidated=True, mode="w-")
-
-    ds = xr.open_zarr(output, concat_characters=False)  # type: ignore[no-untyped-call]
-    if pack:
-        ds = unpack_variables(ds)
-
-    return ds
-
-
-def bgen_to_zarr(
-    input: PathType,
-    output: StoreLike,
-    region: Optional[Mapping[Hashable, Any]] = None,
-    chunk_length: int = 10_000,
-    chunk_width: int = 1_000,
-    temp_chunk_length: int = 100,
-    compressor: Optional[Any] = numcodecs.Blosc(cname="zstd", clevel=7, shuffle=2),
-    probability_dtype: Optional[DType] = "uint8",
-    max_mem: str = "4GB",
-    pack: bool = True,
-    tempdir: Optional[PathType] = None,
-) -> Dataset:
-    """Convert a BGEN file to a Zarr on-disk store.
-
-    This function is a convenience for calling :func:`read_bgen` followed by
-    :func:`rechunk_bgen`.
-
-    Parameters
-    ----------
-    input
-        Path to local BGEN dataset.
-    output
-        Zarr store or path to directory in file system.
-    region
-        Indexers on dataset dimensions used to define a subset of data to convert.
-        Must be None or a dict with keys matching dimension names and values
-        equal to integers or slice objects. This is passed directly to `Dataset.isel`
-        so it has the same semantics.
-    chunk_length
-        Length (number of variants) of chunks in which data are stored, by default 10_000.
-    chunk_width
-        Width (number of samples) to use when storing chunks in output, by default 1_000.
-    temp_chunk_length
-        Length of chunks used in raw BGEN read, by default 100. This defines the vertical
-        chunking (i.e. in the variants dimension) used when reading the raw data and because
-        there is no horizontal chunking at this phase (i.e. in the samples dimension), this
-        value should be much smaller than the target `chunk_length`.
-    compressor
-        Zarr compressor, by default Blosc + zstd with compression level 7. No compression
-        is used when set as None.
-    probability_dtype
-        Data type used to encode genotype probabilities, must be either uint8 or uint16.
-        Setting this parameter results in a loss of precision. If None, probabilities
-        will not be altered when stored.
-    max_mem
-        Deprecated and no longer used. Memory is managed by Dask.
-    pack
-        Whether or not to optimize variable representations by removing unnecessary
-        dimensions and elements. This includes storing 2 genotypes instead of 3, omitting
-        dosage and collapsing the genotype probability mask to 2 dimensions. All of
-        the above are restored in the resulting Dataset at the expense of extra
-        computations on read.
-    tempdir
-        Deprecated and no longer used. No intermediate store is created.
-
-    Warnings
-    --------
-
-    This functional is only applicable to diploid, bi-allelic BGEN datasets.
-
-    Returns
-    -------
-
-    Dataset
-        The rechunked dataset.
-    """
-    ds = read_bgen(input, chunks=(temp_chunk_length, -1, -1))
-    if region is not None:
-        ds = ds.isel(indexers=region)
-    return rechunk_bgen(
-        ds,
-        output,
-        chunk_length=chunk_length,
-        chunk_width=chunk_width,
-        compressor=compressor,
-        probability_dtype=probability_dtype,
-        max_mem=max_mem,
-        pack=pack,
-        tempdir=tempdir,
-    )
diff --git a/sgkit/tests/io/bgen/test_bgen_reader.py b/sgkit/tests/io/bgen/test_bgen_reader.py
index 428014cda..047c72d41 100644
--- a/sgkit/tests/io/bgen/test_bgen_reader.py
+++ b/sgkit/tests/io/bgen/test_bgen_reader.py
@@ -1,21 +1,16 @@
-from pathlib import Path
-from typing import Any, Tuple
+from typing import Tuple
 
-import numcodecs
 import numpy as np
 import numpy.testing as npt
 import pytest
 import xarray as xr
-import zarr
-from zarr.storage import MemoryStore
 
+from sgkit import load_dataset, save_dataset
+from sgkit.io import bgen
 from sgkit.io.bgen.bgen_reader import (
-    GT_DATA_VARS,
     BgenReader,
     _split_alleles,
-    bgen_to_zarr,
     read_bgen,
-    rechunk_bgen,
     unpack_variables,
 )
 
@@ -201,117 +196,54 @@ def test_read_bgen__invalid_chunks(shared_datadir):
         read_bgen(path, chunks=(100, -1))  # type: ignore[arg-type]
 
 
-def _rechunk_bgen(
-    shared_datadir: Path, tmp_path: Path, **kwargs: Any
-) -> Tuple[xr.Dataset, xr.Dataset, str]:
-    path = shared_datadir / "example.bgen"
-    ds = read_bgen(path, chunks=(10, -1, -1))
-    store = tmp_path / "example.zarr"
-    dsr = rechunk_bgen(ds, store, **kwargs)
-    return ds, dsr, str(store)
-
+def test_legacy_conversion_removed():
+    assert bgen.__all__ == ["read_bgen"]
+    for name in ("bgen_to_zarr", "rechunk_bgen"):
+        assert not hasattr(bgen, name)
+        assert not hasattr(bgen.bgen_reader, name)
 
-def _open_zarr(store: str, **kwargs: Any) -> xr.Dataset:
-    # Force concat_characters False to avoid to avoid https://github.com/pydata/xarray/issues/4405
-    return xr.open_zarr(store, concat_characters=False, **kwargs)  # type: ignore[no-any-return,no-untyped-call]
 
-
-@pytest.mark.parametrize("target_chunks", [(10, 10), (50, 50), (100, 50), (50, 100)])
-def test_rechunk_bgen__target_chunks(shared_datadir, tmp_path, target_chunks):
-    _, dsr, store = _rechunk_bgen(
-        shared_datadir,
-        tmp_path,
-        chunk_length=target_chunks[0],
-        chunk_width=target_chunks[1],
-        pack=False,
+def test_read_chunk_and_save_bgen(shared_datadir, tmp_path):
+    ds = read_bgen(shared_datadir / "example.bgen").chunk(
+        {"variants": 100, "samples": 50}
     )
-    for v in GT_DATA_VARS:
-        assert dsr[v].data.chunksize[:2] == target_chunks
-    assert zarr.open_group(store, mode="r").metadata.zarr_format == 2
-
-
-@pytest.mark.parametrize("compressor", [None, numcodecs.Blosc(cname="zstd", clevel=7)])
-def test_rechunk_bgen__compressor(shared_datadir, tmp_path, compressor):
-    _, _, store = _rechunk_bgen(shared_datadir, tmp_path, compressor=compressor)
-    array = zarr.open_group(store, mode="r")["call_genotype_probability"]
-    assert array.compressors == (() if compressor is None else (compressor,))
-
-
-def test_rechunk_bgen__memory_store(shared_datadir):
-    ds = read_bgen(shared_datadir / "example.bgen")
-    store = MemoryStore()
-    dsr = rechunk_bgen(ds, store, probability_dtype=None, pack=False)
-    xr.testing.assert_allclose(ds.compute(), dsr.compute())
-
-
-def test_rechunk_bgen__legacy_memory_options(shared_datadir, tmp_path):
-    with pytest.warns(FutureWarning, match="max_mem and tempdir no longer control"):
-        _rechunk_bgen(shared_datadir, tmp_path, max_mem="1MB", tempdir=tmp_path)
-
-
-def test_rechunk_from_zarr__self_consistent(shared_datadir, tmp_path):
-    # With no probability dtype or packing, rechunk_{to,from}_zarr is a noop
-    ds, dsr, store = _rechunk_bgen(
-        shared_datadir, tmp_path, probability_dtype=None, pack=False
-    )
-    xr.testing.assert_allclose(ds.compute(), dsr.compute())
-
-
-@pytest.mark.parametrize("dtype", ["uint8", "uint16"])
-def test_rechunk_bgen__probability_encoding(shared_datadir, tmp_path, dtype):
-    ds, _, store = _rechunk_bgen(
-        shared_datadir, tmp_path, probability_dtype=dtype, pack=False
-    )
-    dsr = _open_zarr(store, mask_and_scale=False)
-    v = "call_genotype_probability"
-    assert dsr[v].shape == ds[v].shape
-    assert dsr[v].dtype == dtype
-    dsr = _open_zarr(store, mask_and_scale=True)
-    # There are two missing calls which equates to
-    # 6 total nan values across 3 possible genotypes
-    assert np.isnan(dsr[v].values).sum() == 6
-    tolerance = 1.0 / (np.iinfo(dtype).max - 1)
-    np.testing.assert_allclose(ds[v], dsr[v], atol=tolerance)
-
-
-def test_rechunk_bgen__variable_packing(shared_datadir, tmp_path):
-    ds, dsr, store = _rechunk_bgen(
-        shared_datadir, tmp_path, probability_dtype=None, pack=True
+    store = tmp_path / "example.zarr"
+    save_dataset(ds, store)
+    ds2 = load_dataset(store)
+    xr.testing.assert_allclose(ds.compute(), ds2.compute())
+    assert (
+        ds2["call_genotype_probability"].chunks
+        == ds["call_genotype_probability"].chunks
     )
-    # A minor tolerance is necessary here when packing is enabled
-    # because one of the genotype probabilities is constructed from the others
-    xr.testing.assert_allclose(ds.compute(), dsr.compute(), atol=1e-6)
 
 
-@pytest.mark.parametrize("dtype", ["uint32", "int8", "float32"])
-def test_rechunk_bgen__invalid_probability_type(shared_datadir, tmp_path, dtype):
-    with pytest.raises(ValueError, match="Probability integer dtype invalid"):
-        _rechunk_bgen(shared_datadir, tmp_path, probability_dtype=dtype)
-
-
-def test_unpack_variables__invalid_gp_dims(shared_datadir, tmp_path):
-    # Validate that an error is thrown when variables are
-    # unpacked without being packed in the first place
-    _, dsr, store = _rechunk_bgen(shared_datadir, tmp_path, pack=False)
+def test_unpack_variables__invalid_gp_dims(shared_datadir):
     with pytest.raises(
         ValueError,
         match="Expecting variable 'call_genotype_probability' to have genotypes dimension of size 2",
     ):
-        unpack_variables(dsr)
+        unpack_variables(read_bgen(shared_datadir / "example.bgen"))
 
 
-@pytest.mark.parametrize(
-    "region", [None, dict(variants=slice(0, 100)), dict(samples=slice(0, 50))]
-)
-def test_bgen_to_zarr(shared_datadir, tmp_path, region):
-    input = shared_datadir / "example.bgen"
-    output = tmp_path / "example.zarr"
-    ds = bgen_to_zarr(input, output, region=region)
-    expected_dims = {
-        k: EXPECTED_DIMS[k]
-        if region is None or k not in region
-        else region[k].stop - region[k].start
-        for k in EXPECTED_DIMS
-    }
-    actual_dims = {k: v for k, v in ds.sizes.items() if k in expected_dims}
-    assert actual_dims == expected_dims
+@pytest.mark.parametrize("dtype", ["float32", "float64"])
+def test_unpack_variables__legacy_store(shared_datadir, tmp_path, dtype):
+    ds = read_bgen(shared_datadir / "example.bgen")
+    gp = ds["call_genotype_probability"]
+    packed = ds.drop_vars(
+        [
+            "call_genotype_probability",
+            "call_genotype_probability_mask",
+            "call_dosage",
+            "call_dosage_mask",
+        ]
+    ).assign(
+        call_genotype_probability=gp[..., 1:],
+        call_genotype_probability_mask=ds["call_genotype_probability_mask"].any(
+            dim="genotypes"
+        ),
+    )
+    store = tmp_path / "legacy.zarr"
+    save_dataset(packed, store)
+    restored = unpack_variables(load_dataset(store), dtype=dtype)
+    xr.testing.assert_allclose(ds.compute(), restored.compute(), atol=1e-6)
+    assert restored["call_genotype_probability"].dtype == dtype

From 402cca5d1507d531c7686fef4dab0dbe8f0e1195 Mon Sep 17 00:00:00 2001
From: Julianus Pfeuffer <8102638+jpfeuffer@users.noreply.github.com>
Date: Fri, 16 Oct 2026 16:08:09 +0200
Subject: [PATCH 3/7] Decouple legacy BGEN dataset unpacking from cbgen

Expose unpack_variables without the optional BGEN backend, preserve its old import path, and defer native reader imports until BGEN file access. Add blocked-backend import and unpacking regressions, preserve actionable dependency errors, and document the dependency-free API for issue 1331.

Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
---
 docs/api.rst                            |  1 +
 docs/changelog.rst                      |  5 ++
 docs/user_guide.rst                     | 14 ++++-
 sgkit/io/bgen/__init__.py               | 13 +---
 sgkit/io/bgen/bgen_reader.py            | 61 +++++++++---------
 sgkit/io/bgen/utils.py                  | 42 +++++++++++++
 sgkit/tests/io/bgen/test_bgen_reader.py |  2 +-
 sgkit/tests/io/test_bgen_utils.py       | 84 +++++++++++++++++++++++++
 8 files changed, 177 insertions(+), 45 deletions(-)
 create mode 100644 sgkit/io/bgen/utils.py
 create mode 100644 sgkit/tests/io/test_bgen_utils.py

diff --git a/docs/api.rst b/docs/api.rst
index b7fc6e59b..63584557a 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -25,6 +25,7 @@ BGEN
    :toctree: generated/
 
    read_bgen
+   unpack_variables
 
 PLINK
 -----
diff --git a/docs/changelog.rst b/docs/changelog.rst
index 5886f27ba..670138364 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -40,6 +40,11 @@ Deprecations
 Bug fixes
 ~~~~~~~~~
 
+- Unpacking legacy BGEN-derived Zarr datasets no longer imports or requires
+  cbgen. Use :func:`sgkit.io.bgen.unpack_variables`; the original
+  ``sgkit.io.bgen.bgen_reader.unpack_variables`` import is also preserved.
+  The optional native dependency is loaded only when reading BGEN files.
+  (:issue:`1331`)
 - Fixed bug causing high memory usage in :func:`pedigree_kinship` when
   evaluating a chunked relationship matrix with the Hamilton-Kerr method.
   (:user:`timothymillar`, :pr:`1335`, :issue:`1333`)
diff --git a/docs/user_guide.rst b/docs/user_guide.rst
index 942b9ad53..1204b532a 100644
--- a/docs/user_guide.rst
+++ b/docs/user_guide.rst
@@ -104,8 +104,18 @@ memory. This example retains the reader's floating-point genotype probabilities
 and dosages; it does not perform the removed converters' lossy integer
 quantization or variable packing. There are no ``max_mem`` or ``tempdir``
 arguments; those belonged to the removed rechunker-based conversion API.
-The ``unpack_variables`` helper in ``sgkit.io.bgen.bgen_reader`` remains
-available to restore probabilities and dosages from existing packed stores.
+To restore probabilities and dosages from an existing legacy packed store,
+use :func:`sgkit.io.bgen.unpack_variables`. **This does not require cbgen or
+the BGEN extra**, because it operates only on the converted Xarray dataset::
+
+    from sgkit.io.bgen import unpack_variables
+
+    ds = sg.load_dataset("legacy-packed.zarr")
+    ds = unpack_variables(ds)
+
+The original ``sgkit.io.bgen.bgen_reader.unpack_variables`` import remains
+supported without optional BGEN dependencies as well. Only reading a BGEN
+file with ``read_bgen`` needs the optional native reader.
 
 PLINK
 -----
diff --git a/sgkit/io/bgen/__init__.py b/sgkit/io/bgen/__init__.py
index f45ee4ac7..d1c087e5b 100644
--- a/sgkit/io/bgen/__init__.py
+++ b/sgkit/io/bgen/__init__.py
@@ -1,11 +1,4 @@
-try:
-    from .bgen_reader import read_bgen
+from .bgen_reader import read_bgen
+from .utils import unpack_variables
 
-    __all__ = ["read_bgen"]
-except ImportError as e:  # pragma: no cover
-    msg = (
-        "sgkit bgen requirements are not installed.\n\n"
-        "Please install them via pip :\n\n"
-        "  pip install 'sgkit[bgen]'"
-    )
-    raise ImportError(str(e) + "\n\n" + msg) from e
+__all__ = ["read_bgen", "unpack_variables"]
diff --git a/sgkit/io/bgen/bgen_reader.py b/sgkit/io/bgen/bgen_reader.py
index 46142b847..d5a17026b 100644
--- a/sgkit/io/bgen/bgen_reader.py
+++ b/sgkit/io/bgen/bgen_reader.py
@@ -1,7 +1,9 @@
 """BGEN reader implementation (using bgen_reader)"""
+import importlib
 import logging
 import time
 from pathlib import Path
+from types import ModuleType
 from typing import Any, List, Optional, Tuple, Union
 
 import dask
@@ -9,16 +11,29 @@
 import dask.dataframe as dd
 import numpy as np
 import pandas as pd
-import xarray as xr
-from cbgen import bgen_file, bgen_metafile
 from xarray import Dataset
 
 from sgkit import create_genotype_dosage_dataset
+from sgkit.io.bgen.utils import unpack_variables  # noqa: F401
 from sgkit.io.utils import dataframe_to_dict, encode_contigs
 from sgkit.typing import ArrayLike, DType, NDArray, PathType
 
 logger = logging.getLogger(__name__)
 
+
+def _require_cbgen() -> ModuleType:
+    try:
+        return importlib.import_module("cbgen")
+    except ModuleNotFoundError as e:
+        if e.name != "cbgen":
+            raise
+        raise ImportError(
+            "Reading BGEN files requires the optional sgkit bgen dependencies.\n"
+            "Install them with: pip install 'sgkit[bgen]'\n"
+            "Unpacking an existing dataset does not require these dependencies."
+        ) from e
+
+
 METAFILE_DTYPE = dict(
     [
         ("id", "S"),
@@ -41,12 +56,13 @@ def __init__(
         metafile_path: Optional[PathType] = None,
         dtype: DType = "float32",
     ) -> None:
+        cbgen = _require_cbgen()
         self.path = Path(path)
         self.metafile_path = (
             Path(metafile_path) if metafile_path else self.path.with_suffix(".metafile")
         )
 
-        with bgen_file(self.path) as bgen:
+        with cbgen.bgen_file(self.path) as bgen:
             self.n_variants = bgen.nvariants
             self.n_samples = bgen.nsamples
 
@@ -61,7 +77,7 @@ def __init__(
                     f"BGEN metafile generation complete ({stop - start:.0f} seconds)"
                 )
 
-            with bgen_metafile(self.metafile_path) as mf:
+            with cbgen.bgen_metafile(self.metafile_path) as mf:
                 assert self.n_variants == mf.nvariants
                 self.npartitions = mf.npartitions
                 self.partition_size = mf.partition_size
@@ -100,7 +116,8 @@ def __getitem__(self, idx: Any) -> NDArray:
         # Create a list of all offsets into the underlying file at which
         # data for each variant begins
         all_vaddr = []
-        with bgen_metafile(self.metafile_path) as mf:
+        cbgen = _require_cbgen()
+        with cbgen.bgen_metafile(self.metafile_path) as mf:
             for i in range(start_partition, end_partition + 1):
                 partition = mf.read_partition(i)
                 start_offset = start_partition_offset if i == start_partition else 0
@@ -115,7 +132,7 @@ def __getitem__(self, idx: Any) -> NDArray:
         # Read the probabilities for each variant, apply indexer for
         # samples dimension to give probabilities for all genotypes,
         # and then apply final genotype dimension indexer
-        with bgen_file(self.path) as bgen:
+        with cbgen.bgen_file(self.path) as bgen:
             res = None
             for i, vaddr in enumerate(all_vaddr):
                 probs = bgen.read_probability(vaddr, precision=self.precision)[idx[1]]
@@ -137,7 +154,8 @@ def _split_alleles(allele_ids: bytes) -> List[bytes]:
 
 
 def _read_metafile_partition(path: Path, partition: int) -> pd.DataFrame:
-    with bgen_metafile(path) as mf:
+    cbgen = _require_cbgen()
+    with cbgen.bgen_metafile(path) as mf:
         part = mf.read_partition(partition)
     v = part.variants
     allele_ids = np.array([_split_alleles(aid) for aid in v.allele_ids])
@@ -155,7 +173,8 @@ def _read_metafile_partition(path: Path, partition: int) -> pd.DataFrame:
 
 def read_metafile(path: PathType) -> dd.DataFrame:
     """Read cbgen metafile containing partitioned variant info"""
-    with bgen_metafile(path) as mf:
+    cbgen = _require_cbgen()
+    with cbgen.bgen_metafile(path) as mf:
         divisions = [mf.partition_size * i for i in range(mf.npartitions)] + [
             mf.nvariants - 1
         ]
@@ -304,7 +323,8 @@ def read_bgen(
 
 def _default_sample_ids(path: PathType) -> ArrayLike:
     """Fetch or generate sample ids"""
-    with bgen_file(path) as bgen:
+    cbgen = _require_cbgen()
+    with cbgen.bgen_file(path) as bgen:
         if bgen.contain_samples:
             return bgen.read_samples()
         else:
@@ -317,26 +337,3 @@ def _to_dosage(probs: ArrayLike) -> ArrayLike:
         probs.shape[-1] == 3
     ), f"Expecting genotype (trailing) dimension of size 3, got array of shape {probs.shape}"
     return probs[..., 1] + 2 * probs[..., 2]
-
-
-def unpack_variables(ds: Dataset, dtype: DType = "float32") -> Dataset:
-    """Restore probabilities and dosages from legacy packed BGEN-derived stores."""
-    # Restore homozygous reference GP
-    gp = ds["call_genotype_probability"].astype(dtype)
-    if gp.sizes["genotypes"] != 2:
-        raise ValueError(
-            "Expecting variable 'call_genotype_probability' to have genotypes "
-            f"dimension of size 2 (received sizes = {dict(gp.sizes)})"
-        )
-    ds = ds.drop_vars("call_genotype_probability")
-    ds["call_genotype_probability"] = xr.concat(
-        [1 - gp.sum(dim="genotypes", skipna=False), gp], dim="genotypes"
-    )
-
-    # Restore dosage
-    ds["call_dosage"] = gp[..., 0] + 2 * gp[..., 1]
-    ds["call_dosage_mask"] = ds["call_genotype_probability_mask"]
-    ds["call_genotype_probability_mask"] = ds[
-        "call_genotype_probability_mask"
-    ].broadcast_like(ds["call_genotype_probability"])
-    return ds
diff --git a/sgkit/io/bgen/utils.py b/sgkit/io/bgen/utils.py
new file mode 100644
index 000000000..e6795c7ee
--- /dev/null
+++ b/sgkit/io/bgen/utils.py
@@ -0,0 +1,42 @@
+import xarray as xr
+from xarray import Dataset
+
+from sgkit.typing import DType
+
+
+def unpack_variables(ds: Dataset, dtype: DType = "float32") -> Dataset:
+    """Restore probabilities and dosages from a legacy packed BGEN-derived dataset.
+
+    This operates on an existing Xarray dataset and requires no BGEN reader or
+    optional BGEN dependencies.
+
+    Parameters
+    ----------
+    ds
+        Dataset containing two stored genotype probabilities per call and a
+        two-dimensional ``call_genotype_probability_mask``.
+    dtype
+        Floating-point dtype for the restored probabilities, by default float32.
+
+    Returns
+    -------
+    Dataset
+        Dataset with all three genotype probabilities, dosage and their masks.
+    """
+    gp = ds["call_genotype_probability"].astype(dtype)
+    if gp.sizes["genotypes"] != 2:
+        raise ValueError(
+            "Expecting variable 'call_genotype_probability' to have genotypes "
+            f"dimension of size 2 (received sizes = {dict(gp.sizes)})"
+        )
+    ds = ds.drop_vars("call_genotype_probability")
+    ds["call_genotype_probability"] = xr.concat(
+        [1 - gp.sum(dim="genotypes", skipna=False), gp], dim="genotypes"
+    )
+
+    ds["call_dosage"] = gp[..., 0] + 2 * gp[..., 1]
+    ds["call_dosage_mask"] = ds["call_genotype_probability_mask"]
+    ds["call_genotype_probability_mask"] = ds[
+        "call_genotype_probability_mask"
+    ].broadcast_like(ds["call_genotype_probability"])
+    return ds
diff --git a/sgkit/tests/io/bgen/test_bgen_reader.py b/sgkit/tests/io/bgen/test_bgen_reader.py
index 047c72d41..e82835c63 100644
--- a/sgkit/tests/io/bgen/test_bgen_reader.py
+++ b/sgkit/tests/io/bgen/test_bgen_reader.py
@@ -197,7 +197,7 @@ def test_read_bgen__invalid_chunks(shared_datadir):
 
 
 def test_legacy_conversion_removed():
-    assert bgen.__all__ == ["read_bgen"]
+    assert bgen.__all__ == ["read_bgen", "unpack_variables"]
     for name in ("bgen_to_zarr", "rechunk_bgen"):
         assert not hasattr(bgen, name)
         assert not hasattr(bgen.bgen_reader, name)
diff --git a/sgkit/tests/io/test_bgen_utils.py b/sgkit/tests/io/test_bgen_utils.py
new file mode 100644
index 000000000..ce607381d
--- /dev/null
+++ b/sgkit/tests/io/test_bgen_utils.py
@@ -0,0 +1,84 @@
+import subprocess
+import sys
+import textwrap
+
+import pytest
+
+from sgkit.io.bgen import unpack_variables
+from sgkit.io.bgen.bgen_reader import _require_cbgen
+from sgkit.io.bgen.bgen_reader import unpack_variables as legacy_unpack_variables
+from sgkit.io.bgen.utils import unpack_variables as utility_unpack_variables
+
+
+def test_unpack_variables_import_paths():
+    assert unpack_variables is legacy_unpack_variables
+    assert unpack_variables is utility_unpack_variables
+
+
+def test_unpack_variables_without_cbgen():
+    code = textwrap.dedent(
+        """
+        import importlib.abc
+        import sys
+
+        class BlockCbgen(importlib.abc.MetaPathFinder):
+            def find_spec(self, fullname, path=None, target=None):
+                if fullname == "cbgen" or fullname.startswith("cbgen."):
+                    raise AssertionError("Unpacking must not import cbgen")
+
+        sys.meta_path.insert(0, BlockCbgen())
+
+        import numpy as np
+        import xarray as xr
+        from sgkit.io.bgen import unpack_variables, read_bgen
+        from sgkit.io.bgen.bgen_reader import unpack_variables as legacy_unpack
+        from sgkit.io.bgen.utils import unpack_variables as utility_unpack
+
+        assert unpack_variables is legacy_unpack is utility_unpack
+        ds = xr.Dataset({
+            "call_genotype_probability": (
+                ("variants", "samples", "genotypes"),
+                [[[0.25, 0.5], [np.nan, np.nan]]],
+            ),
+            "call_genotype_probability_mask": (
+                ("variants", "samples"), [[False, True]]
+            ),
+        }).chunk({"variants": 1, "samples": 1})
+        result = unpack_variables(ds)
+        assert result.call_genotype_probability.chunks is not None
+        np.testing.assert_allclose(
+            result.call_genotype_probability.compute(),
+            [[[0.25, 0.25, 0.5], [np.nan, np.nan, np.nan]]],
+        )
+        np.testing.assert_allclose(result.call_dosage.compute(), [[1.25, np.nan]])
+        np.testing.assert_array_equal(result.call_dosage_mask, [[False, True]])
+        np.testing.assert_array_equal(
+            result.call_genotype_probability_mask,
+            [[[False, False, False], [True, True, True]]],
+        )
+        assert "cbgen" not in sys.modules
+        """
+    )
+    subprocess.run(
+        [sys.executable, "-c", code], check=True, capture_output=True, text=True
+    )
+
+
+@pytest.mark.parametrize("missing_module", ["cbgen", "backend_dependency"])
+def test_bgen_missing_backend(monkeypatch, missing_module):
+    def missing_import(name):
+        assert name == "cbgen"
+        raise ModuleNotFoundError(
+            f"No module named '{missing_module}'", name=missing_module
+        )
+
+    monkeypatch.setattr(
+        "sgkit.io.bgen.bgen_reader.importlib.import_module", missing_import
+    )
+    if missing_module == "cbgen":
+        with pytest.raises(ImportError, match=r"pip install 'sgkit\[bgen\]'"):
+            _require_cbgen()
+    else:
+        with pytest.raises(ModuleNotFoundError) as exc:
+            _require_cbgen()
+        assert exc.value.name == missing_module

From 8b7f89587e411cf0c23534c5e0619ba9c983237d Mon Sep 17 00:00:00 2001
From: Julianus Pfeuffer <8102638+jpfeuffer@users.noreply.github.com>
Date: Fri, 16 Oct 2026 16:20:13 +0200
Subject: [PATCH 4/7] Remove native BGEN reader and cbgen dependency

Delegate BGEN conversion to bio2zarr, remove the bgen extra and reader-only fixtures, and update dependency locking and wheel CI. Retain only dependency-free legacy unpacking and its compatibility import. Document the packed-store signature, reconstruction, missingness, lazy execution, and when not to unpack.

Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
---
 .github/scripts/test_sgkit.py                 |  23 ++
 .github/scripts/test_sgkit_bgen.py            |  11 -
 .github/workflows/build-gpu.yml               |   2 +-
 .github/workflows/wheels.yml                  |   6 +-
 README.md                                     |   9 +-
 docs/api.rst                                  |  11 +-
 docs/changelog.rst                            |  17 +-
 docs/user_guide.rst                           |  92 ++---
 pyproject.toml                                |   7 +-
 sgkit/io/bgen/__init__.py                     |   3 +-
 sgkit/io/bgen/bgen_reader.py                  | 342 +-----------------
 sgkit/io/bgen/utils.py                        |  58 ++-
 sgkit/io/utils.py                             |  17 +-
 sgkit/stats/conversion.py                     |   3 +-
 sgkit/tests/io/bgen/__init__.py               |   0
 sgkit/tests/io/bgen/data/.gitignore           |   2 -
 .../io/bgen/data/example-no-samples.bgen      | Bin 17334 -> 0 bytes
 .../bgen/data/example-separate-samples.bgen   | Bin 17402 -> 0 bytes
 .../bgen/data/example-separate-samples.sample |   7 -
 sgkit/tests/io/bgen/data/example.bgen         | Bin 665108 -> 0 bytes
 sgkit/tests/io/bgen/data/samples              |   5 -
 sgkit/tests/io/bgen/test_bgen_reader.py       | 249 -------------
 sgkit/tests/io/test_bgen_utils.py             |  94 ++++-
 uv.lock                                       |  65 +---
 24 files changed, 240 insertions(+), 783 deletions(-)
 delete mode 100644 .github/scripts/test_sgkit_bgen.py
 delete mode 100644 sgkit/tests/io/bgen/__init__.py
 delete mode 100644 sgkit/tests/io/bgen/data/.gitignore
 delete mode 100644 sgkit/tests/io/bgen/data/example-no-samples.bgen
 delete mode 100644 sgkit/tests/io/bgen/data/example-separate-samples.bgen
 delete mode 100644 sgkit/tests/io/bgen/data/example-separate-samples.sample
 delete mode 100644 sgkit/tests/io/bgen/data/example.bgen
 delete mode 100644 sgkit/tests/io/bgen/data/samples
 delete mode 100644 sgkit/tests/io/bgen/test_bgen_reader.py

diff --git a/.github/scripts/test_sgkit.py b/.github/scripts/test_sgkit.py
index 1ad14f2e2..2f62e7dd3 100644
--- a/.github/scripts/test_sgkit.py
+++ b/.github/scripts/test_sgkit.py
@@ -1,5 +1,28 @@
+from importlib.metadata import metadata, requires
+
+import xarray as xr
+
 import sgkit as sg
+from sgkit.io import bgen
 
 if __name__ == "__main__":
     ds = sg.simulate_genotype_call_dataset(n_variant=100, n_sample=50, n_contig=23)
     print(ds)
+    assert bgen.__all__ == ["unpack_variables"]
+    assert "bgen" not in metadata("sgkit").get_all("Provides-Extra", [])
+    assert not any("cbgen" in requirement for requirement in requires("sgkit"))
+    packed = xr.Dataset(
+        {
+            "call_genotype_probability": (
+                ("variants", "samples", "genotypes"),
+                [[[0.25, 0.5]]],
+            ),
+            "call_genotype_probability_mask": (
+                ("variants", "samples"),
+                [[False]],
+            ),
+        }
+    )
+    unpacked = bgen.unpack_variables(packed)
+    assert unpacked.call_genotype_probability.values.tolist() == [[[0.25, 0.25, 0.5]]]
+    assert unpacked.call_dosage.item() == 1.25
diff --git a/.github/scripts/test_sgkit_bgen.py b/.github/scripts/test_sgkit_bgen.py
deleted file mode 100644
index 1d0a334c0..000000000
--- a/.github/scripts/test_sgkit_bgen.py
+++ /dev/null
@@ -1,11 +0,0 @@
-import urllib.request
-
-from sgkit.io.bgen import read_bgen
-
-if __name__ == "__main__":
-    urllib.request.urlretrieve(
-        "https://github.com/sgkit-dev/sgkit/raw/main/sgkit/tests/io/bgen/data/example.bgen",
-        "example.bgen",
-    )
-    ds = read_bgen("example.bgen")
-    print(ds)
diff --git a/.github/workflows/build-gpu.yml b/.github/workflows/build-gpu.yml
index fcb021b89..d9f30a0a2 100644
--- a/.github/workflows/build-gpu.yml
+++ b/.github/workflows/build-gpu.yml
@@ -49,7 +49,7 @@ jobs:
         run: |
           conda install -c nvidia cudatoolkit
           # Avoid building SciPy from source in CI.
-          uv pip install --only-binary scipy --python "$CONDA_PREFIX/bin/python" -e ".[bgen,plink]" --group test
+          uv pip install --only-binary scipy --python "$CONDA_PREFIX/bin/python" -e ".[plink]" --group test
 
       - name: Numba Information
         run: |
diff --git a/.github/workflows/wheels.yml b/.github/workflows/wheels.yml
index 8450fc622..b725e1420 100644
--- a/.github/workflows/wheels.yml
+++ b/.github/workflows/wheels.yml
@@ -81,9 +81,8 @@ jobs:
           # Avoid building SciPy from source in CI.
           wheel=$(ls artifact/sgkit-*.whl)
           uv venv --python "${{ matrix.python-version }}"
-          uv pip install --python .venv --only-binary scipy "${wheel}[bgen,plink]"
+          uv pip install --python .venv --only-binary scipy "${wheel}[plink]"
           uv run --no-sync python sgkit-copy/.github/scripts/test_sgkit.py
-          uv run --no-sync python sgkit-copy/.github/scripts/test_sgkit_bgen.py
           uv run --no-sync python sgkit-copy/.github/scripts/test_sgkit_plink.py
 
   windows-test:
@@ -120,9 +119,8 @@ jobs:
           # Avoid building SciPy from source in CI.
           $wheel = (Get-ChildItem artifact/sgkit-*.whl).FullName
           uv venv --python "${{ matrix.python-version }}"
-          uv pip install --python .venv --only-binary scipy "${wheel}[bgen,plink]"
+          uv pip install --python .venv --only-binary scipy "${wheel}[plink]"
           uv run --no-sync python sgkit-copy/.github/scripts/test_sgkit.py
-          uv run --no-sync python sgkit-copy/.github/scripts/test_sgkit_bgen.py
           uv run --no-sync python sgkit-copy/.github/scripts/test_sgkit_plink.py
 
 
diff --git a/README.md b/README.md
index 629a68c5f..89ee63c08 100644
--- a/README.md
+++ b/README.md
@@ -12,10 +12,11 @@ For more information on using sgkit, see the [documentation](https://sgkit-dev.g
 
 **Genetic file conversion:** Use [bio2zarr](https://sgkit-dev.github.io/bio2zarr/)
 to convert genetic file formats to Zarr, then load them with `sgkit.load_dataset`.
-The deprecated `bgen_to_zarr` and `rechunk_bgen` functions have been removed.
-Bio2zarr's BGEN support is [still pending](https://github.com/sgkit-dev/bio2zarr/issues/417);
-see the [BGEN migration guide](docs/user_guide.rst#bgen) for the interim
-`read_bgen` / Xarray `chunk` / `save_dataset` workflow.
+The BGEN reader, conversion functions and `bgen` extra have been removed;
+sgkit no longer depends on cbgen. Use a bio2zarr version with BGEN support
+(tracked in [bio2zarr issue 417](https://github.com/sgkit-dev/bio2zarr/issues/417)).
+See the [BGEN migration guide](docs/user_guide.rst#bgen) for details and
+`unpack_variables`, retained only for existing legacy packed Zarr stores.
 
 [//]: # (numfocus-fiscal-sponsor-attribution)
 
diff --git a/docs/api.rst b/docs/api.rst
index 63584557a..85a8c519b 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -12,19 +12,20 @@ See :ref:`reading_and_writing_genetic_data`
 .. important::
 
    **Use bio2zarr for genetic file format conversion to Zarr**, then load the
-   converted dataset with :func:`sgkit.load_dataset`. The deprecated BGEN
-   conversion functions ``bgen_to_zarr`` and ``rechunk_bgen`` have been removed.
-   BGEN support in bio2zarr is still pending; see :ref:`bgen_conversion_migration`
-   for the interim read/chunk/save workflow.
+   converted dataset with :func:`sgkit.load_dataset`. The BGEN reader and
+   conversion functions have been removed. See :ref:`bgen_conversion_migration`
+   for migration and legacy-store unpacking guidance.
 
 BGEN
 -----
 
+Only the helper for existing legacy packed stores remains; it does not read
+BGEN files or require an optional backend.
+
 .. currentmodule:: sgkit.io.bgen
 .. autosummary::
    :toctree: generated/
 
-   read_bgen
    unpack_variables
 
 PLINK
diff --git a/docs/changelog.rst b/docs/changelog.rst
index 670138364..cf764e3eb 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -16,15 +16,15 @@ Breaking changes
 
 - Require Zarr Python >= 3 and Xarray >= 2026.9.0. The default on-disk Zarr
   format remains 2. (:issue:`1355`)
-- **Remove the deprecated BGEN conversion functions** ``sgkit.io.bgen.bgen_to_zarr``
-  and ``sgkit.io.bgen.rechunk_bgen``, along with their rechunker dependency.
+- **Remove BGEN reading and conversion**: ``sgkit.io.bgen.read_bgen``,
+  ``sgkit.io.bgen.bgen_to_zarr`` and ``sgkit.io.bgen.rechunk_bgen``, along with
+  the ``bgen`` extra and the cbgen and rechunker dependencies.
   **Use bio2zarr for genetic file format conversion to Zarr**, and load the
-  result with :func:`load_dataset`. BGEN support in bio2zarr is still pending
+  result with :func:`load_dataset`. BGEN input requires a bio2zarr version
+  with BGEN support
   (`bio2zarr issue 417 <https://github.com/sgkit-dev/bio2zarr/issues/417>`_).
-  Until then, BGEN users can call :func:`sgkit.io.bgen.read_bgen`,
-  :meth:`xarray.Dataset.chunk`, and :func:`save_dataset` explicitly; this does
-  not reproduce the old probability quantization, packing, or ``max_mem``/
-  ``tempdir`` controls. See :ref:`bgen_conversion_migration`.
+  The dependency-free :func:`sgkit.io.bgen.unpack_variables` helper remains
+  for existing legacy packed stores. See :ref:`bgen_conversion_migration`.
   (:pr:`1325`, :issue:`1355`)
 
 Deprecations
@@ -43,7 +43,8 @@ Bug fixes
 - Unpacking legacy BGEN-derived Zarr datasets no longer imports or requires
   cbgen. Use :func:`sgkit.io.bgen.unpack_variables`; the original
   ``sgkit.io.bgen.bgen_reader.unpack_variables`` import is also preserved.
-  The optional native dependency is loaded only when reading BGEN files.
+  Its documentation explains the legacy packing convention and when unpacking
+  is needed; ordinary unpacked datasets and new bio2zarr output do not need it.
   (:issue:`1331`)
 - Fixed bug causing high memory usage in :func:`pedigree_kinship` when
   evaluating a chunked relationship matrix with the Hamilton-Kerr method.
diff --git a/docs/user_guide.rst b/docs/user_guide.rst
index 1204b532a..9f8e079b5 100644
--- a/docs/user_guide.rst
+++ b/docs/user_guide.rst
@@ -20,28 +20,25 @@ Reading and writing genetic data
    `bio2zarr documentation <https://sgkit-dev.github.io/bio2zarr/>`_ for
    installation and conversion instructions.
 
-   The deprecated BGEN conversion functions ``bgen_to_zarr`` and ``rechunk_bgen``
-   have been removed. BGEN conversion in bio2zarr is still pending; BGEN users
-   should follow :ref:`bgen_conversion_migration` in the meantime.
+   BGEN reading and conversion have been removed from sgkit, along with the
+   optional cbgen dependency. See :ref:`bgen_conversion_migration` for conversion
+   guidance and support for existing legacy packed stores.
 
 .. _installation:
 
 Installation
 ------------
 
-Sgkit can read standard genetic file formats, including PLINK and BGEN. For reading VCF,
-please use the `bio2zarr <https://github.com/sgkit-dev/bio2zarr>`_ package.
+Sgkit reads Zarr datasets directly. For VCF, BGEN and PLINK conversion, use
+`bio2zarr <https://github.com/sgkit-dev/bio2zarr>`_. The deprecated direct PLINK
+reader remains available with optional dependencies.
 
-If sgkit has been installed using conda, support for reading BGEN and PLINK is included.
+If sgkit has been installed using conda, support for reading PLINK is included.
 
-If sgkit has been installed using pip, then support for reading these formats is
+If sgkit has been installed using pip, then support for reading PLINK is
 not included, and requires additional dependencies, which can be installed
 as an "extra" feature using pip, as follows.
 
-To install sgkit with BGEN support::
-
-    $ pip install 'sgkit[bgen]'
-
 To install sgkit with PLINK support::
 
     $ pip install 'sgkit[plink]'
@@ -51,10 +48,10 @@ Converting genetic data to Zarr
 
 Genetic file format conversion belongs in
 `bio2zarr <https://sgkit-dev.github.io/bio2zarr/>`__, rather than sgkit.
-Convert VCF and PLINK inputs with bio2zarr before analysis, so the expensive
-conversion step need only be paid once. The direct ``read_X`` functions are
-convenience functions for small inputs or cases where the cost of reading is small;
-the PLINK functions are deprecated.
+Convert inputs with bio2zarr before analysis, so the expensive conversion step
+need only be paid once. BGEN input requires a bio2zarr version with BGEN support
+(see :ref:`bgen_conversion_migration`). The remaining direct PLINK functions
+are deprecated convenience functions for small inputs.
 
 After converting a file to Zarr format, it can be loaded with sgkit's :func:`sgkit.load_dataset`.
 This is like Xarray's :func:`xarray.open_zarr` function, with some useful defaults applied for you.
@@ -79,43 +76,52 @@ which makes opening the dataset faster.
 BGEN
 ----
 
-The :func:`sgkit.io.bgen.read_bgen` function loads a single BGEN dataset as Dask
-arrays within an :class:`xarray.Dataset` from a ``bgen`` file.
-
 .. warning::
 
-   ``sgkit.io.bgen.bgen_to_zarr`` and ``sgkit.io.bgen.rechunk_bgen`` have been
-   removed. New format-conversion workflows should use bio2zarr, but
-   **bio2zarr does not yet support BGEN input**. Progress is tracked in
-   `bio2zarr issue 417 <https://github.com/sgkit-dev/bio2zarr/issues/417>`_.
+   ``sgkit.io.bgen.read_bgen``, ``sgkit.io.bgen.bgen_to_zarr`` and
+   ``sgkit.io.bgen.rechunk_bgen`` have been removed, together with the ``bgen``
+   extra. Sgkit no longer reads BGEN files or depends on cbgen.
 
-Until BGEN support is available in bio2zarr, the equivalent read/chunk/save
-steps can be performed explicitly::
+Use bio2zarr for BGEN conversion, then load the resulting Zarr dataset with
+:func:`sgkit.load_dataset`. Install a bio2zarr version that includes BGEN support;
+availability is tracked in
+`bio2zarr issue 417 <https://github.com/sgkit-dev/bio2zarr/issues/417>`_.
+An older bio2zarr release without BGEN support cannot replace the removed reader.
+Sgkit does not provide an alternative BGEN conversion path.
 
-    import sgkit as sg
-    from sgkit.io.bgen import read_bgen
+Legacy packed stores
+~~~~~~~~~~~~~~~~~~~~
 
-    ds = read_bgen("input.bgen")
-    ds = ds.chunk({"variants": 10000, "samples": 1000})
-    sg.save_dataset(ds, "output.zarr")
-
-Choose chunk sizes and Dask scheduler settings appropriate to the available
-memory. This example retains the reader's floating-point genotype probabilities
-and dosages; it does not perform the removed converters' lossy integer
-quantization or variable packing. There are no ``max_mem`` or ``tempdir``
-arguments; those belonged to the removed rechunker-based conversion API.
-To restore probabilities and dosages from an existing legacy packed store,
-use :func:`sgkit.io.bgen.unpack_variables`. **This does not require cbgen or
-the BGEN extra**, because it operates only on the converted Xarray dataset::
+Some older sgkit BGEN converters packed variables to reduce storage size:
+they saved only the heterozygous and homozygous-alternate probabilities,
+omitted dosage, and used one missingness flag per variant/sample pair.
+For these **known legacy packed stores only**, use
+:func:`sgkit.io.bgen.unpack_variables` after loading and before methods that
+expect complete genotype probabilities or dosage. This helper operates on an
+existing Xarray dataset and needs no BGEN backend::
 
+    import sgkit as sg
     from sgkit.io.bgen import unpack_variables
 
-    ds = sg.load_dataset("legacy-packed.zarr")
-    ds = unpack_variables(ds)
-
+    packed = sg.load_dataset("legacy-packed.zarr")
+    ds = unpack_variables(packed)
+
+The expected signature is ``call_genotype_probability`` with dimensions
+``(variants, samples, genotypes)`` and **two** stored probabilities, plus
+``call_genotype_probability_mask`` with dimensions ``(variants, samples)``.
+Unpacking restores three diploid, biallelic genotype probabilities, computes
+alternate-allele dosage, and expands the probability mask. For example,
+``[0.25, 0.5]`` becomes ``[0.25, 0.25, 0.5]`` with dosage ``1.25``.
+Missing probabilities remain NaN. The input is unchanged and Dask arrays
+remain lazy; lost quantization precision cannot be recovered.
+
+**Do not unpack ordinary datasets, new bio2zarr output, or an already-unpacked
+store.** A two-state probability array alone is not evidence of legacy packing:
+other ploidies or allele counts can also produce two states. The helper is not
+a general BGEN decoder or schema adapter. :func:`sgkit.load_dataset` does not
+automatically detect or unpack legacy stores.
 The original ``sgkit.io.bgen.bgen_reader.unpack_variables`` import remains
-supported without optional BGEN dependencies as well. Only reading a BGEN
-file with ``read_bgen`` needs the optional native reader.
+supported as a compatibility alias; that module no longer contains a reader.
 
 PLINK
 -----
diff --git a/pyproject.toml b/pyproject.toml
index dfd0ab5f1..a0cd46283 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -41,7 +41,6 @@ content-type = "text/x-rst"
 
 [project.optional-dependencies]
 plink = ["partd", "bed-reader"]
-bgen = ["cbgen > 1.0.5"]
 
 [dependency-groups]
 test = [
@@ -62,7 +61,7 @@ test = [
   "aiohttp",
   "requests",
   "graphviz",
-  "sgkit[plink,bgen]",
+  "sgkit[plink]",
 ]
 docs = [
   "graphviz",
@@ -189,10 +188,6 @@ ignore_missing_imports = true
 module = ["sklearn.*"]
 ignore_missing_imports = true
 
-[[tool.mypy.overrides]]
-module = ["cbgen.*"]
-ignore_missing_imports = true
-
 [[tool.mypy.overrides]]
 module = ["bed_reader.*"]
 ignore_missing_imports = true
diff --git a/sgkit/io/bgen/__init__.py b/sgkit/io/bgen/__init__.py
index d1c087e5b..abaaba5bd 100644
--- a/sgkit/io/bgen/__init__.py
+++ b/sgkit/io/bgen/__init__.py
@@ -1,4 +1,3 @@
-from .bgen_reader import read_bgen
 from .utils import unpack_variables
 
-__all__ = ["read_bgen", "unpack_variables"]
+__all__ = ["unpack_variables"]
diff --git a/sgkit/io/bgen/bgen_reader.py b/sgkit/io/bgen/bgen_reader.py
index d5a17026b..72857bc8d 100644
--- a/sgkit/io/bgen/bgen_reader.py
+++ b/sgkit/io/bgen/bgen_reader.py
@@ -1,339 +1,9 @@
-"""BGEN reader implementation (using bgen_reader)"""
-import importlib
-import logging
-import time
-from pathlib import Path
-from types import ModuleType
-from typing import Any, List, Optional, Tuple, Union
+"""Compatibility import for unpacking legacy stores; BGEN reading was removed.
 
-import dask
-import dask.array as da
-import dask.dataframe as dd
-import numpy as np
-import pandas as pd
-from xarray import Dataset
+Use bio2zarr to convert BGEN inputs and :func:`sgkit.load_dataset` to load Zarr.
+New code should import :func:`sgkit.io.bgen.unpack_variables` directly.
+"""
 
-from sgkit import create_genotype_dosage_dataset
-from sgkit.io.bgen.utils import unpack_variables  # noqa: F401
-from sgkit.io.utils import dataframe_to_dict, encode_contigs
-from sgkit.typing import ArrayLike, DType, NDArray, PathType
+from .utils import unpack_variables
 
-logger = logging.getLogger(__name__)
-
-
-def _require_cbgen() -> ModuleType:
-    try:
-        return importlib.import_module("cbgen")
-    except ModuleNotFoundError as e:
-        if e.name != "cbgen":
-            raise
-        raise ImportError(
-            "Reading BGEN files requires the optional sgkit bgen dependencies.\n"
-            "Install them with: pip install 'sgkit[bgen]'\n"
-            "Unpacking an existing dataset does not require these dependencies."
-        ) from e
-
-
-METAFILE_DTYPE = dict(
-    [
-        ("id", "S"),
-        ("rsid", "S"),
-        ("chrom", "S"),
-        ("pos", "int32"),
-        ("a1", "S"),
-        ("a2", "S"),
-        ("offset", "int64"),
-    ]
-)
-
-
-class BgenReader:
-    name = "bgen_reader"
-
-    def __init__(
-        self,
-        path: PathType,
-        metafile_path: Optional[PathType] = None,
-        dtype: DType = "float32",
-    ) -> None:
-        cbgen = _require_cbgen()
-        self.path = Path(path)
-        self.metafile_path = (
-            Path(metafile_path) if metafile_path else self.path.with_suffix(".metafile")
-        )
-
-        with cbgen.bgen_file(self.path) as bgen:
-            self.n_variants = bgen.nvariants
-            self.n_samples = bgen.nsamples
-
-            if not self.metafile_path.exists():
-                start = time.time()
-                logger.info(
-                    f"Generating BGEN metafile for '{self.path}' (this may take a while)"
-                )
-                bgen.create_metafile(self.metafile_path, verbose=False)
-                stop = time.time()
-                logger.info(
-                    f"BGEN metafile generation complete ({stop - start:.0f} seconds)"
-                )
-
-            with cbgen.bgen_metafile(self.metafile_path) as mf:
-                assert self.n_variants == mf.nvariants
-                self.npartitions = mf.npartitions
-                self.partition_size = mf.partition_size
-
-        self.shape = (self.n_variants, self.n_samples, 3)
-        self.dtype = np.dtype(dtype)
-        self.precision = 64 if self.dtype.itemsize >= 8 else 32
-        self.ndim = 3
-
-    def __getitem__(self, idx: Any) -> NDArray:
-        if not isinstance(idx, tuple):
-            raise IndexError(f"Indexer must be tuple (received {type(idx)})")
-        if len(idx) != self.ndim:
-            raise IndexError(
-                f"Indexer must have {self.ndim} items (received {len(idx)} slices)"
-            )
-        if not all(isinstance(i, slice) or isinstance(i, int) for i in idx):
-            raise IndexError(
-                f"Indexer must contain only slices or ints (received types {[type(i) for i in idx]})"
-            )
-        # Determine which dims should have unit size in result
-        squeeze_dims = tuple(i for i in range(len(idx)) if isinstance(idx[i], int))
-        # Convert all indexers to slices
-        idx = tuple(slice(i, i + 1) if isinstance(i, int) else i for i in idx)
-
-        if idx[0].start == idx[0].stop:
-            return np.empty((0,) * self.ndim, dtype=self.dtype)
-
-        # Determine start and end partitions that correspond to the
-        # given variant dimension indexer
-        start_partition = idx[0].start // self.partition_size
-        start_partition_offset = idx[0].start % self.partition_size
-        end_partition = (idx[0].stop - 1) // self.partition_size
-        end_partition_offset = (idx[0].stop - 1) % self.partition_size
-
-        # Create a list of all offsets into the underlying file at which
-        # data for each variant begins
-        all_vaddr = []
-        cbgen = _require_cbgen()
-        with cbgen.bgen_metafile(self.metafile_path) as mf:
-            for i in range(start_partition, end_partition + 1):
-                partition = mf.read_partition(i)
-                start_offset = start_partition_offset if i == start_partition else 0
-                end_offset = (
-                    end_partition_offset + 1
-                    if i == end_partition
-                    else self.partition_size
-                )
-                vaddr = partition.variants.offset
-                all_vaddr.extend(vaddr[start_offset:end_offset].tolist())
-
-        # Read the probabilities for each variant, apply indexer for
-        # samples dimension to give probabilities for all genotypes,
-        # and then apply final genotype dimension indexer
-        with cbgen.bgen_file(self.path) as bgen:
-            res = None
-            for i, vaddr in enumerate(all_vaddr):
-                probs = bgen.read_probability(vaddr, precision=self.precision)[idx[1]]
-                assert len(probs.shape) == 2 and probs.shape[1] == 3
-                if res is None:
-                    res = np.zeros((len(all_vaddr), len(probs), 3), dtype=self.dtype)
-                res[i] = probs
-            res = res[..., idx[2]]  # type: ignore[index]
-            return np.squeeze(res, axis=squeeze_dims)  # type: ignore[arg-type]
-
-
-def _split_alleles(allele_ids: bytes) -> List[bytes]:
-    alleles = allele_ids.split(b",")
-    if len(alleles) != 2:
-        raise NotImplementedError(
-            f"Bgen reads only supported for biallelic variants (found non-biallelic variant '{str(allele_ids)}')"
-        )
-    return alleles
-
-
-def _read_metafile_partition(path: Path, partition: int) -> pd.DataFrame:
-    cbgen = _require_cbgen()
-    with cbgen.bgen_metafile(path) as mf:
-        part = mf.read_partition(partition)
-    v = part.variants
-    allele_ids = np.array([_split_alleles(aid) for aid in v.allele_ids])
-    data = {
-        "id": v.id,
-        "rsid": v.rsid,
-        "chrom": v.chromosome,
-        "pos": v.position,
-        "a1": allele_ids[:, 0],
-        "a2": allele_ids[:, 1],
-        "offset": v.offset,
-    }
-    return pd.DataFrame(data).astype(METAFILE_DTYPE)
-
-
-def read_metafile(path: PathType) -> dd.DataFrame:
-    """Read cbgen metafile containing partitioned variant info"""
-    cbgen = _require_cbgen()
-    with cbgen.bgen_metafile(path) as mf:
-        divisions = [mf.partition_size * i for i in range(mf.npartitions)] + [
-            mf.nvariants - 1
-        ]
-        dfs = [
-            dask.delayed(_read_metafile_partition)(path, i)
-            for i in range(mf.npartitions)
-        ]
-        meta = dd.utils.make_meta(METAFILE_DTYPE)
-        return dd.from_delayed(dfs, meta=meta, divisions=divisions, verify_meta=False)
-
-
-def read_samples(path: PathType) -> pd.DataFrame:
-    """Read BGEN .sample file"""
-    df = pd.read_csv(path, sep=" ", skiprows=[1], usecols=[0])
-    df.columns = ["sample_id"]
-    return df
-
-
-def read_bgen(
-    path: PathType,
-    metafile_path: Optional[PathType] = None,
-    sample_path: Optional[PathType] = None,
-    chunks: Union[str, int, Tuple[int, int, int]] = "auto",
-    lock: bool = False,
-    persist: bool = True,
-    contig_dtype: DType = "str",
-    gp_dtype: DType = "float32",
-) -> Dataset:
-    """Read BGEN dataset.
-
-    Loads a single BGEN dataset as dask arrays within a Dataset
-    from a ``.bgen`` file.
-
-    Parameters
-    ----------
-    path
-        Path to BGEN file.
-    metafile_path
-        Path to companion index file used to determine BGEN byte offsets.
-        Defaults to ``path`` + ".metafile" if not provided.
-        This file is necessary for reading BGEN genotype probabilities and it will be
-        generated the first time the file is read if it does not already exist.
-        If it needs to be created, it can make the first call to this function
-        much slower than subsequent calls.
-    sample_path
-        Path to ``.sample`` file, by default None. This is used to fetch sample identifiers
-        and when provided it is preferred over sample identifiers embedded in the ``.bgen`` file.
-    chunks
-        Chunk size for genotype probability data (3 dimensions),
-        by default "auto".
-    lock
-        Whether or not to synchronize concurrent reads of
-        file blocks, by default False. This is passed through to
-        [dask.array.from_array](https://docs.dask.org/en/latest/array-api.html#dask.array.from_array).
-    persist
-        Whether or not to persist variant information in memory, by default True.
-        This is an important performance consideration as the metadata file for this data will
-        be read multiple times when False.
-    contig_dtype
-        Data type for contig names, by default "str".
-        This may also be an integer type (e.g. "int"), but will fail if any of the contig names
-        cannot be converted to integers.
-    gp_dtype
-        Data type for genotype probabilities, by default "float32".
-
-    Warnings
-    --------
-    Only bi-allelic, diploid BGEN files are currently supported.
-
-    Returns
-    -------
-    A dataset containing the following variables:
-
-    - :data:`sgkit.variables.variant_id_spec` (variants)
-    - :data:`sgkit.variables.variant_contig_spec` (variants)
-    - :data:`sgkit.variables.variant_position_spec` (variants)
-    - :data:`sgkit.variables.variant_allele_spec` (variants)
-    - :data:`sgkit.variables.sample_id_spec` (samples)
-    - :data:`sgkit.variables.call_dosage_spec` (variants, samples)
-    - :data:`sgkit.variables.call_dosage_mask_spec` (variants, samples)
-    - :data:`sgkit.variables.call_genotype_probability_spec` (variants, samples, genotypes)
-    - :data:`sgkit.variables.call_genotype_probability_mask_spec` (variants, samples, genotypes)
-
-    """
-    if isinstance(chunks, tuple) and len(chunks) != 3:
-        raise ValueError(f"`chunks` must be tuple with 3 items, not {chunks}")
-    if not np.issubdtype(gp_dtype, np.floating):
-        raise ValueError(
-            f"`gp_dtype` must be a floating point data type, not {gp_dtype}"
-        )
-    if not np.issubdtype(contig_dtype, np.integer) and np.dtype(
-        contig_dtype
-    ).kind not in {"U", "S"}:
-        raise ValueError(
-            f"`contig_dtype` must be of string or int type, not {contig_dtype}"
-        )
-
-    with dask.config.set({"dataframe.convert-string": False}):
-        path = Path(path)
-        sample_path = Path(sample_path) if sample_path else path.with_suffix(".sample")
-
-        if sample_path.exists():
-            sample_id = read_samples(sample_path).sample_id.values.astype("U")
-        else:
-            sample_id = _default_sample_ids(path)
-
-        bgen_reader = BgenReader(path, metafile_path=metafile_path, dtype=gp_dtype)
-
-        df = read_metafile(bgen_reader.metafile_path)
-        if persist:
-            df = df.persist()
-        arrs = dataframe_to_dict(df, METAFILE_DTYPE)
-
-        variant_id = arrs["id"]
-        variant_contig: ArrayLike = arrs["chrom"].astype(contig_dtype)
-        variant_contig, variant_contig_names = encode_contigs(variant_contig)
-        variant_contig_names = list(variant_contig_names)
-        variant_position = arrs["pos"]
-        variant_allele = da.hstack(
-            (arrs["a1"][:, np.newaxis], arrs["a2"][:, np.newaxis])
-        )
-
-        call_genotype_probability = da.from_array(
-            bgen_reader,
-            chunks=chunks,
-            lock=lock,
-            fancy=False,
-            asarray=False,
-            name=f"{bgen_reader.name}:read_bgen:{path}",
-        )
-        call_dosage = _to_dosage(call_genotype_probability)
-
-        ds: Dataset = create_genotype_dosage_dataset(
-            variant_contig_names=variant_contig_names,
-            variant_contig=variant_contig,
-            variant_position=variant_position,
-            variant_allele=variant_allele,
-            sample_id=sample_id,
-            call_dosage=call_dosage,
-            call_genotype_probability=call_genotype_probability,
-            variant_id=variant_id,
-        )
-
-        return ds
-
-
-def _default_sample_ids(path: PathType) -> ArrayLike:
-    """Fetch or generate sample ids"""
-    cbgen = _require_cbgen()
-    with cbgen.bgen_file(path) as bgen:
-        if bgen.contain_samples:
-            return bgen.read_samples()
-        else:
-            return np.char.add(b"sample_", np.arange(bgen.nsamples).astype("S"))  # type: ignore[no-untyped-call]
-
-
-def _to_dosage(probs: ArrayLike) -> ArrayLike:
-    """Calculate the dosage from genotype likelihoods (probabilities)"""
-    assert (
-        probs.shape[-1] == 3
-    ), f"Expecting genotype (trailing) dimension of size 3, got array of shape {probs.shape}"
-    return probs[..., 1] + 2 * probs[..., 2]
+__all__ = ["unpack_variables"]
diff --git a/sgkit/io/bgen/utils.py b/sgkit/io/bgen/utils.py
index e6795c7ee..bb042dea1 100644
--- a/sgkit/io/bgen/utils.py
+++ b/sgkit/io/bgen/utils.py
@@ -7,21 +7,67 @@
 def unpack_variables(ds: Dataset, dtype: DType = "float32") -> Dataset:
     """Restore probabilities and dosages from a legacy packed BGEN-derived dataset.
 
-    This operates on an existing Xarray dataset and requires no BGEN reader or
-    optional BGEN dependencies.
+    Use this only for stores written with variable packing by sgkit's removed
+    ``bgen_to_zarr`` or ``rechunk_bgen`` functions. Packing saved space by
+    omitting the homozygous-reference probability, storing a single missingness
+    flag per call, and omitting dosage (which can be derived from probabilities).
+    Unpack such a dataset before using methods that expect full genotype
+    probabilities or dosage.
+
+    This is not a BGEN reader, a general probability decoder, or a required step
+    after loading Zarr. Do not apply it to ordinary unpacked datasets or new
+    bio2zarr output. A ``genotypes`` dimension of length two is meaningful here
+    only for this legacy diploid, biallelic packing convention, not for haploid
+    or multiallelic data.
 
     Parameters
     ----------
     ds
-        Dataset containing two stored genotype probabilities per call and a
-        two-dimensional ``call_genotype_probability_mask``.
+        Legacy packed dataset with ``call_genotype_probability`` dimensions
+        ``(variants, samples, genotypes)``, where ``genotypes`` has length two
+        and stores the heterozygous and homozygous-alternate probabilities,
+        in that order. ``call_genotype_probability_mask`` must have dimensions
+        ``(variants, samples)`` and be True for missing calls; the stored
+        probabilities for those calls are NaN.
     dtype
-        Floating-point dtype for the restored probabilities, by default float32.
+        Floating-point dtype for restored probabilities and dosage, by default
+        float32. This cannot recover precision lost during legacy quantization.
 
     Returns
     -------
     Dataset
-        Dataset with all three genotype probabilities, dosage and their masks.
+        New dataset with three genotype probabilities ordered as
+        homozygous-reference, heterozygous, homozygous-alternate; alternate-allele
+        ``call_dosage``; and their masks. Other variables and attributes are
+        preserved. The input dataset is not modified.
+
+    Raises
+    ------
+    ValueError
+        If the stored ``genotypes`` dimension does not have length two. An
+        already-unpacked dataset must not be unpacked a second time.
+
+    Notes
+    -----
+    The omitted probability is reconstructed as ``1 - p_het - p_hom_alt``.
+    Dosage is ``p_het + 2 * p_hom_alt``. Missing probabilities remain NaN,
+    and the per-call mask is broadcast across all three genotypes. No hard
+    genotype calls are inferred. Operations remain lazy for Dask-backed arrays
+    and require no optional BGEN backend.
+
+    Examples
+    --------
+    Load a known legacy packed store and unpack it once before analysis::
+
+        import sgkit as sg
+        from sgkit.io.bgen import unpack_variables
+
+        packed = sg.load_dataset("legacy-packed.zarr")
+        ds = unpack_variables(packed)
+
+    For example, stored probabilities ``[0.25, 0.5]`` become
+    ``[0.25, 0.25, 0.5]`` and alternate-allele dosage ``1.25``. Loading with
+    :func:`sgkit.load_dataset` alone does not perform this reconstruction.
     """
     gp = ds["call_genotype_probability"].astype(dtype)
     if gp.sizes["genotypes"] != 2:
diff --git a/sgkit/io/utils.py b/sgkit/io/utils.py
index 49f2df8ec..48e6206c1 100644
--- a/sgkit/io/utils.py
+++ b/sgkit/io/utils.py
@@ -1,10 +1,10 @@
-from typing import Mapping, Optional, Tuple
+from typing import Mapping, Optional
 
 import dask.dataframe as dd
 import numpy as np
 
 from ..typing import ArrayLike, DType
-from ..utils import encode_array, max_str_len
+from ..utils import max_str_len
 
 INT_MISSING, INT_FILL = -1, -2
 
@@ -37,16 +37,3 @@ def dataframe_to_dict(
             dt = f"{kind}{max_len}"
         arrs[c] = a.astype(dt)
     return arrs
-
-
-def encode_contigs(contig: ArrayLike) -> Tuple[ArrayLike, ArrayLike]:
-    # TODO: test preservation of int16
-    # If contigs are already integers, use them as-is
-    if np.issubdtype(contig.dtype, np.integer):
-        ids = contig
-        names = np.unique(np.asarray(ids)).astype(str)  # type: ignore[no-untyped-call]
-    # Otherwise create index for contig names based
-    # on order of appearance in underlying file
-    else:
-        ids, names = encode_array(np.asarray(contig, dtype=str))
-    return ids, names
diff --git a/sgkit/stats/conversion.py b/sgkit/stats/conversion.py
index 3d2ebf529..ce5aaeeb9 100644
--- a/sgkit/stats/conversion.py
+++ b/sgkit/stats/conversion.py
@@ -137,7 +137,8 @@ def convert_probability_to_call(
     Parameters
     ----------
     ds
-        Dataset containing genotype probabilities, such as from :func:`sgkit.io.bgen.read_bgen`.
+        Dataset containing diploid biallelic genotype probabilities. For legacy
+        packed BGEN-derived stores, first use :func:`sgkit.io.bgen.unpack_variables`.
     call_genotype_probability
         Genotype probability variable to be converted as defined by
         :data:`sgkit.variables.call_genotype_probability_spec`.
diff --git a/sgkit/tests/io/bgen/__init__.py b/sgkit/tests/io/bgen/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/sgkit/tests/io/bgen/data/.gitignore b/sgkit/tests/io/bgen/data/.gitignore
deleted file mode 100644
index 4685de1c2..000000000
--- a/sgkit/tests/io/bgen/data/.gitignore
+++ /dev/null
@@ -1,2 +0,0 @@
-*.metadata2.mmm
-*.metafile
diff --git a/sgkit/tests/io/bgen/data/example-no-samples.bgen b/sgkit/tests/io/bgen/data/example-no-samples.bgen
deleted file mode 100644
index e8b88ed701490d6810a47d666dbd81b96bb21e74..0000000000000000000000000000000000000000
GIT binary patch
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diff --git a/sgkit/tests/io/bgen/data/example-separate-samples.bgen b/sgkit/tests/io/bgen/data/example-separate-samples.bgen
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diff --git a/sgkit/tests/io/bgen/data/example-separate-samples.sample b/sgkit/tests/io/bgen/data/example-separate-samples.sample
deleted file mode 100644
index c6e7b1b26..000000000
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diff --git a/sgkit/tests/io/bgen/data/example.bgen b/sgkit/tests/io/bgen/data/example.bgen
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diff --git a/sgkit/tests/io/bgen/data/samples b/sgkit/tests/io/bgen/data/samples
deleted file mode 100644
index 44dbc30ea..000000000
--- a/sgkit/tests/io/bgen/data/samples
+++ /dev/null
@@ -1,5 +0,0 @@
-sample_001
-sample_002
-sample_003
-sample_004
-sample_005
diff --git a/sgkit/tests/io/bgen/test_bgen_reader.py b/sgkit/tests/io/bgen/test_bgen_reader.py
deleted file mode 100644
index e82835c63..000000000
--- a/sgkit/tests/io/bgen/test_bgen_reader.py
+++ /dev/null
@@ -1,249 +0,0 @@
-from typing import Tuple
-
-import numpy as np
-import numpy.testing as npt
-import pytest
-import xarray as xr
-
-from sgkit import load_dataset, save_dataset
-from sgkit.io import bgen
-from sgkit.io.bgen.bgen_reader import (
-    BgenReader,
-    _split_alleles,
-    read_bgen,
-    unpack_variables,
-)
-
-CHUNKS = [
-    (100, 200, 3),
-    (100, 200, 1),
-    (100, 500, 3),
-    (199, 500, 3),
-    ((100, 99), 500, 2),
-    "auto",
-]
-INDEXES = [0, 10, 20, 100, -1]
-
-# Expectations below generated using bgen-reader directly, ex:
-# > from bgen_reader import open_bgen
-# > bgen = open_bgen('sgkit_bgen/tests/data/example.bgen', verbose=False)
-# > bgen.read(-1)[0] # Probabilities for last variant, first sample
-# array([[0.0133972 , 0.98135378, 0.00524902]]
-# > bgen.allele_expectation(-1)[0, 0, -1] # Dosage for last variant, first sample
-# 0.9918518217727197
-EXPECTED_PROBABILITIES = np.array(
-    [  # Generated using bgen-reader directly
-        [np.nan, np.nan, np.nan],
-        [0.007, 0.966, 0.0259],
-        [0.993, 0.002, 0.003],
-        [0.916, 0.007, 0.0765],
-        [0.013, 0.981, 0.0052],
-    ]
-)
-EXPECTED_DOSAGES = np.array(
-    [np.nan, 1.018, 0.010, 0.160, 0.991]  # Generated using bgen-reader directly
-)
-
-EXPECTED_DIMS = dict(variants=199, samples=500, genotypes=3, alleles=2)
-
-
-def _shape(*dims: str) -> Tuple[int, ...]:
-    return tuple(EXPECTED_DIMS[d] for d in dims)
-
-
-@pytest.mark.parametrize("chunks", CHUNKS)
-def test_read_bgen(shared_datadir, chunks):
-    path = shared_datadir / "example.bgen"
-    ds = read_bgen(path, chunks=chunks)
-
-    # check some of the data (in different chunks)
-    assert ds["call_dosage"].shape == _shape("variants", "samples")
-    npt.assert_almost_equal(ds["call_dosage"].values[1][0], 1.987, decimal=3)
-    npt.assert_almost_equal(ds["call_dosage"].values[100][0], 0.160, decimal=3)
-    npt.assert_array_equal(ds["call_dosage_mask"].values[0, 0], [True])
-    npt.assert_array_equal(ds["call_dosage_mask"].values[0, 1], [False])
-    assert ds["call_genotype_probability"].shape == _shape(
-        "variants", "samples", "genotypes"
-    )
-    npt.assert_almost_equal(
-        ds["call_genotype_probability"].values[1][0], [0.005, 0.002, 0.992], decimal=3
-    )
-    npt.assert_almost_equal(
-        ds["call_genotype_probability"].values[100][0], [0.916, 0.007, 0.076], decimal=3
-    )
-    npt.assert_array_equal(
-        ds["call_genotype_probability_mask"].values[0, 0], [True] * 3
-    )
-    npt.assert_array_equal(
-        ds["call_genotype_probability_mask"].values[0, 1], [False] * 3
-    )
-
-
-def test_read_bgen__with_sample_file(shared_datadir):
-    # The example file was generated using
-    # qctool -g sgkit_bgen/tests/data/example.bgen -og sgkit_bgen/tests/data/example-separate-samples.bgen -os sgkit_bgen/tests/data/example-separate-samples.sample -incl-samples sgkit_bgen/tests/data/samples
-    # Then editing example-separate-samples.sample to change the sample IDs
-    path = shared_datadir / "example-separate-samples.bgen"
-    ds = read_bgen(path)
-    # Check the sample IDs are the ones from the .sample file
-    assert ds["sample_id"].values.tolist() == ["s1", "s2", "s3", "s4", "s5"]
-
-
-def test_read_bgen__with_no_samples(shared_datadir):
-    # The example file was generated using
-    # qctool -g sgkit_bgen/tests/data/example.bgen -og sgkit_bgen/tests/data/example-no-samples.bgen -os sgkit_bgen/tests/data/example-no-samples.sample -bgen-omit-sample-identifier-block -incl-samples sgkit_bgen/tests/data/samples
-    # Then deleting example-no-samples.sample
-    path = shared_datadir / "example-no-samples.bgen"
-    ds = read_bgen(path)
-    # Check the sample IDs are generated
-    assert ds["sample_id"].values.tolist() == [
-        b"sample_0",
-        b"sample_1",
-        b"sample_2",
-        b"sample_3",
-        b"sample_4",
-    ]
-
-
-@pytest.mark.parametrize("dtype", ["f2", "f4", "f8"])
-def test_read_bgen__gp_dtype(shared_datadir, dtype):
-    path = shared_datadir / "example.bgen"
-    ds = read_bgen(path, gp_dtype=dtype)
-    dtype = np.dtype(dtype)
-    assert ds["call_genotype_probability"].dtype == dtype
-    assert ds["call_dosage"].dtype == dtype
-
-
-@pytest.mark.parametrize("dtype", ["c8", "i8", "str"])
-def test_read_bgen__invalid_gp_dtype(shared_datadir, dtype):
-    path = shared_datadir / "example.bgen"
-    with pytest.raises(
-        ValueError, match="`gp_dtype` must be a floating point data type"
-    ):
-        read_bgen(path, gp_dtype=dtype)
-
-
-@pytest.mark.parametrize("dtype", ["U", "S", "u1", "u2", "i8", "int"])
-def test_read_bgen__contig_dtype(shared_datadir, dtype):
-    path = shared_datadir / "example.bgen"
-    ds = read_bgen(path, contig_dtype=dtype)
-    dtype = np.dtype(dtype)
-    if dtype.kind in {"U", "S"}:
-        assert ds["variant_contig"].dtype == np.int64  # type: ignore[comparison-overlap]
-    else:
-        assert ds["variant_contig"].dtype == dtype
-
-
-@pytest.mark.parametrize("dtype", ["c8", "M", "f4"])
-def test_read_bgen__invalid_contig_dtype(shared_datadir, dtype):
-    path = shared_datadir / "example.bgen"
-    with pytest.raises(
-        ValueError, match="`contig_dtype` must be of string or int type"
-    ):
-        read_bgen(path, contig_dtype=dtype)
-
-
-@pytest.mark.parametrize("chunks", CHUNKS)
-def test_read_bgen__fancy_index(shared_datadir, chunks):
-    path = shared_datadir / "example.bgen"
-    ds = read_bgen(path, chunks=chunks)
-    npt.assert_almost_equal(
-        ds["call_genotype_probability"][INDEXES, 0], EXPECTED_PROBABILITIES, decimal=3
-    )
-    npt.assert_almost_equal(ds["call_dosage"][INDEXES, 0], EXPECTED_DOSAGES, decimal=3)
-
-
-@pytest.mark.parametrize("chunks", CHUNKS)
-def test_read_bgen__scalar_index(shared_datadir, chunks):
-    path = shared_datadir / "example.bgen"
-    ds = read_bgen(path, chunks=chunks)
-    for i, ix in enumerate(INDEXES):
-        npt.assert_almost_equal(
-            ds["call_genotype_probability"][ix, 0], EXPECTED_PROBABILITIES[i], decimal=3
-        )
-        npt.assert_almost_equal(
-            ds["call_dosage"][ix, 0], EXPECTED_DOSAGES[i], decimal=3
-        )
-        for j in range(3):
-            npt.assert_almost_equal(
-                ds["call_genotype_probability"][ix, 0, j],
-                EXPECTED_PROBABILITIES[i, j],
-                decimal=3,
-            )
-
-
-def test_read_bgen__raise_on_invalid_indexers(shared_datadir):
-    path = shared_datadir / "example.bgen"
-    reader = BgenReader(path)
-    with pytest.raises(IndexError, match="Indexer must be tuple"):
-        reader[[0]]
-    with pytest.raises(IndexError, match="Indexer must have 3 items"):
-        reader[(slice(None),)]
-    with pytest.raises(IndexError, match="Indexer must contain only slices or ints"):
-        reader[([0], [0], [0])]
-
-
-def test_split_alleles__raise_on_multiallelic():
-    with pytest.raises(
-        NotImplementedError, match="Bgen reads only supported for biallelic variants"
-    ):
-        _split_alleles(b"A,B,C")
-
-
-def test_read_bgen__invalid_chunks(shared_datadir):
-    path = shared_datadir / "example.bgen"
-    with pytest.raises(ValueError, match="`chunks` must be tuple with 3 items"):
-        read_bgen(path, chunks=(100, -1))  # type: ignore[arg-type]
-
-
-def test_legacy_conversion_removed():
-    assert bgen.__all__ == ["read_bgen", "unpack_variables"]
-    for name in ("bgen_to_zarr", "rechunk_bgen"):
-        assert not hasattr(bgen, name)
-        assert not hasattr(bgen.bgen_reader, name)
-
-
-def test_read_chunk_and_save_bgen(shared_datadir, tmp_path):
-    ds = read_bgen(shared_datadir / "example.bgen").chunk(
-        {"variants": 100, "samples": 50}
-    )
-    store = tmp_path / "example.zarr"
-    save_dataset(ds, store)
-    ds2 = load_dataset(store)
-    xr.testing.assert_allclose(ds.compute(), ds2.compute())
-    assert (
-        ds2["call_genotype_probability"].chunks
-        == ds["call_genotype_probability"].chunks
-    )
-
-
-def test_unpack_variables__invalid_gp_dims(shared_datadir):
-    with pytest.raises(
-        ValueError,
-        match="Expecting variable 'call_genotype_probability' to have genotypes dimension of size 2",
-    ):
-        unpack_variables(read_bgen(shared_datadir / "example.bgen"))
-
-
-@pytest.mark.parametrize("dtype", ["float32", "float64"])
-def test_unpack_variables__legacy_store(shared_datadir, tmp_path, dtype):
-    ds = read_bgen(shared_datadir / "example.bgen")
-    gp = ds["call_genotype_probability"]
-    packed = ds.drop_vars(
-        [
-            "call_genotype_probability",
-            "call_genotype_probability_mask",
-            "call_dosage",
-            "call_dosage_mask",
-        ]
-    ).assign(
-        call_genotype_probability=gp[..., 1:],
-        call_genotype_probability_mask=ds["call_genotype_probability_mask"].any(
-            dim="genotypes"
-        ),
-    )
-    store = tmp_path / "legacy.zarr"
-    save_dataset(packed, store)
-    restored = unpack_variables(load_dataset(store), dtype=dtype)
-    xr.testing.assert_allclose(ds.compute(), restored.compute(), atol=1e-6)
-    assert restored["call_genotype_probability"].dtype == dtype
diff --git a/sgkit/tests/io/test_bgen_utils.py b/sgkit/tests/io/test_bgen_utils.py
index ce607381d..fcdd4164b 100644
--- a/sgkit/tests/io/test_bgen_utils.py
+++ b/sgkit/tests/io/test_bgen_utils.py
@@ -2,10 +2,13 @@
 import sys
 import textwrap
 
+import numpy as np
 import pytest
+import xarray as xr
 
+from sgkit import load_dataset, save_dataset
+from sgkit.io import bgen
 from sgkit.io.bgen import unpack_variables
-from sgkit.io.bgen.bgen_reader import _require_cbgen
 from sgkit.io.bgen.bgen_reader import unpack_variables as legacy_unpack_variables
 from sgkit.io.bgen.utils import unpack_variables as utility_unpack_variables
 
@@ -15,6 +18,16 @@ def test_unpack_variables_import_paths():
     assert unpack_variables is utility_unpack_variables
 
 
+def test_bgen_reader_removed():
+    from sgkit.io.bgen import bgen_reader
+
+    assert bgen.__all__ == ["unpack_variables"]
+    assert bgen_reader.__all__ == ["unpack_variables"]
+    for module in (bgen, bgen_reader):
+        for name in ("read_bgen", "BgenReader", "bgen_to_zarr", "rechunk_bgen"):
+            assert not hasattr(module, name)
+
+
 def test_unpack_variables_without_cbgen():
     code = textwrap.dedent(
         """
@@ -30,7 +43,7 @@ def find_spec(self, fullname, path=None, target=None):
 
         import numpy as np
         import xarray as xr
-        from sgkit.io.bgen import unpack_variables, read_bgen
+        from sgkit.io.bgen import unpack_variables
         from sgkit.io.bgen.bgen_reader import unpack_variables as legacy_unpack
         from sgkit.io.bgen.utils import unpack_variables as utility_unpack
 
@@ -64,21 +77,66 @@ def find_spec(self, fullname, path=None, target=None):
     )
 
 
-@pytest.mark.parametrize("missing_module", ["cbgen", "backend_dependency"])
-def test_bgen_missing_backend(monkeypatch, missing_module):
-    def missing_import(name):
-        assert name == "cbgen"
-        raise ModuleNotFoundError(
-            f"No module named '{missing_module}'", name=missing_module
-        )
+@pytest.fixture
+def packed_dataset():
+    return xr.Dataset(
+        {
+            "call_genotype_probability": (
+                ("variants", "samples", "genotypes"),
+                [[[0.25, 0.5], [np.nan, np.nan]], [[0.0, 1.0], [0.0, 0.0]]],
+            ),
+            "call_genotype_probability_mask": (
+                ("variants", "samples"),
+                [[False, True], [False, False]],
+            ),
+            "variant_position": ("variants", [10, 20]),
+            "sample_id": ("samples", ["a", "b"]),
+        },
+        attrs={"source": "legacy packed BGEN store"},
+    ).chunk({"variants": 1, "samples": 1})
+
 
-    monkeypatch.setattr(
-        "sgkit.io.bgen.bgen_reader.importlib.import_module", missing_import
+@pytest.mark.parametrize("dtype", ["float32", "float64"])
+@pytest.mark.parametrize("zarr_format", [2, 3])
+def test_unpack_variables_legacy_store(packed_dataset, tmp_path, dtype, zarr_format):
+    store = tmp_path / "legacy.zarr"
+    consolidated = zarr_format == 2
+    save_dataset(
+        packed_dataset, store, zarr_format=zarr_format, consolidated=consolidated
+    )
+    packed = load_dataset(store, consolidated=consolidated)
+    before = packed.copy(deep=True)
+    restored = unpack_variables(packed, dtype=dtype)
+    assert restored.call_genotype_probability.chunks is not None
+    assert restored.call_dosage.chunks is not None
+    assert restored.call_genotype_probability.dtype == dtype
+    assert restored.call_dosage.dtype == dtype
+    np.testing.assert_allclose(
+        restored.call_genotype_probability.compute(),
+        [
+            [[0.25, 0.25, 0.5], [np.nan, np.nan, np.nan]],
+            [[0.0, 0.0, 1.0], [1.0, 0.0, 0.0]],
+        ],
+    )
+    np.testing.assert_allclose(restored.call_dosage.compute(), [[1.25, np.nan], [2, 0]])
+    xr.testing.assert_equal(
+        restored.call_dosage_mask,
+        packed.call_genotype_probability_mask.rename("call_dosage_mask"),
     )
-    if missing_module == "cbgen":
-        with pytest.raises(ImportError, match=r"pip install 'sgkit\[bgen\]'"):
-            _require_cbgen()
-    else:
-        with pytest.raises(ModuleNotFoundError) as exc:
-            _require_cbgen()
-        assert exc.value.name == missing_module
+    np.testing.assert_array_equal(
+        restored.call_genotype_probability_mask,
+        [[[False] * 3, [True] * 3], [[False] * 3, [False] * 3]],
+    )
+    xr.testing.assert_identical(restored.sample_id, packed.sample_id)
+    xr.testing.assert_identical(restored.variant_position, packed.variant_position)
+    assert restored.attrs == packed.attrs
+    xr.testing.assert_identical(packed, before)
+
+
+def test_unpack_variables_rejects_unpacked_dataset(packed_dataset):
+    restored = unpack_variables(packed_dataset)
+    with pytest.raises(
+        ValueError,
+        match="Expecting variable 'call_genotype_probability' to have genotypes dimension of size 2",
+    ):
+        unpack_variables(restored)
diff --git a/uv.lock b/uv.lock
index cadff5fda..acd9c31d9 100644
--- a/uv.lock
+++ b/uv.lock
@@ -191,15 +191,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/7e/b3/6b4067be973ae96ba0d615946e314c5ae35f9f993eca561b356540bb0c2b/alabaster-1.0.0-py3-none-any.whl", hash = "sha256:fc6786402dc3fcb2de3cabd5fe455a2db534b371124f1f21de8731783dec828b", size = 13929, upload-time = "2024-07-26T18:15:02.05Z" },
 ]
 
-[[package]]
-name = "appdirs"
-version = "1.4.4"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/d7/d8/05696357e0311f5b5c316d7b95f46c669dd9c15aaeecbb48c7d0aeb88c40/appdirs-1.4.4.tar.gz", hash = "sha256:7d5d0167b2b1ba821647616af46a749d1c653740dd0d2415100fe26e27afdf41", size = 13470, upload-time = "2020-05-11T07:59:51.037Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/3b/00/2344469e2084fb287c2e0b57b72910309874c3245463acd6cf5e3db69324/appdirs-1.4.4-py2.py3-none-any.whl", hash = "sha256:a841dacd6b99318a741b166adb07e19ee71a274450e68237b4650ca1055ab128", size = 9566, upload-time = "2020-05-11T07:59:49.499Z" },
-]
-
 [[package]]
 name = "appnope"
 version = "1.0.0"
@@ -320,34 +311,6 @@ version = "0.3.1"
 source = { registry = "https://pypi.org/simple" }
 sdist = { url = "https://files.pythonhosted.org/packages/7c/a9/cc2ee5fb2686292610e743324854059a6da6780479fa38999d725bd729ab/callee-0.3.1.tar.gz", hash = "sha256:056f95d7760c87ce470aa4ab83bab5f9bdf090d4ecf77d52efe9c4559c0aefd3", size = 19824, upload-time = "2019-12-24T14:58:38.579Z" }
 
-[[package]]
-name = "cbgen"
-version = "1.0.6"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "appdirs" },
-    { name = "cffi" },
-    { name = "numpy" },
-    { name = "pooch" },
-    { name = "pytest" },
-    { name = "urllib3" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/a0/97/cc69e0d0accb46965332ae247f3289832e546f8d30cb77218d6eb0f47b48/cbgen-1.0.6.tar.gz", hash = "sha256:edcf856c9b0cafae7f6e999ed5d08aacdf1e09dadec766b79990fe5861e8cf7e", size = 12387, upload-time = "2024-06-17T15:27:30.503Z" }
-wheels = [
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-]
-
 [[package]]
 name = "certifi"
 version = "2026.7.22"
@@ -3084,20 +3047,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746", size = 20538, upload-time = "2025-05-15T12:30:06.134Z" },
 ]
 
-[[package]]
-name = "pooch"
-version = "1.9.0"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "packaging" },
-    { name = "platformdirs" },
-    { name = "requests" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/83/43/85ef45e8b36c6a48546af7b266592dc32d7f67837a6514d111bced6d7d75/pooch-1.9.0.tar.gz", hash = "sha256:de46729579b9857ffd3e741987a2f6d5e0e03219892c167c6578c0091fb511ed", size = 61788, upload-time = "2026-01-30T19:15:09.649Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/2a/2d/d4bf65e47cea8ff2c794a600c4fd1273a7902f268757c531e0ee9f18aa58/pooch-1.9.0-py3-none-any.whl", hash = "sha256:f265597baa9f760d25ceb29d0beb8186c243d6607b0f60b83ecf14078dbc703b", size = 67175, upload-time = "2026-01-30T19:15:08.36Z" },
-]
-
 [[package]]
 name = "pre-commit"
 version = "4.6.2"
@@ -4013,9 +3962,6 @@ dependencies = [
 ]
 
 [package.optional-dependencies]
-bgen = [
-    { name = "cbgen" },
-]
 plink = [
     { name = "bed-reader" },
     { name = "partd" },
@@ -4047,7 +3993,7 @@ dev = [
     { name = "scanpydoc", version = "0.17.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "scikit-allel" },
     { name = "seaborn" },
-    { name = "sgkit", extra = ["bgen", "plink"] },
+    { name = "sgkit", extra = ["plink"] },
     { name = "sphinx" },
     { name = "sphinx-autodoc-typehints" },
     { name = "sphinx-copybutton" },
@@ -4092,7 +4038,7 @@ test = [
     { name = "pytest-mock" },
     { name = "requests" },
     { name = "scikit-allel" },
-    { name = "sgkit", extra = ["bgen", "plink"] },
+    { name = "sgkit", extra = ["plink"] },
     { name = "statsmodels" },
     { name = "yarl" },
 ]
@@ -4100,7 +4046,6 @@ test = [
 [package.metadata]
 requires-dist = [
     { name = "bed-reader", marker = "extra == 'plink'" },
-    { name = "cbgen", marker = "extra == 'bgen'", specifier = ">1.0.5" },
     { name = "dask", extras = ["array", "dataframe"], specifier = ">=2022.1.0,<=2024.8.0" },
     { name = "fsspec", specifier = "!=2021.6.*" },
     { name = "numba" },
@@ -4113,7 +4058,7 @@ requires-dist = [
     { name = "xarray", specifier = ">=2026.9.0" },
     { name = "zarr", specifier = ">=3" },
 ]
-provides-extras = ["plink", "bgen"]
+provides-extras = ["plink"]
 
 [package.metadata.requires-dev]
 dev = [
@@ -4140,7 +4085,7 @@ dev = [
     { name = "scanpydoc" },
     { name = "scikit-allel" },
     { name = "seaborn" },
-    { name = "sgkit", extras = ["plink", "bgen"] },
+    { name = "sgkit", extras = ["plink"] },
     { name = "sphinx", specifier = "<9.0.0" },
     { name = "sphinx-autodoc-typehints" },
     { name = "sphinx-copybutton" },
@@ -4180,7 +4125,7 @@ test = [
     { name = "pytest-mock" },
     { name = "requests" },
     { name = "scikit-allel" },
-    { name = "sgkit", extras = ["plink", "bgen"] },
+    { name = "sgkit", extras = ["plink"] },
     { name = "statsmodels" },
     { name = "yarl" },
 ]

From aed7547660d5e9d78f1728f67608ea0ea49d0d48 Mon Sep 17 00:00:00 2001
From: Julianus Pfeuffer <8102638+jpfeuffer@users.noreply.github.com>
Date: Fri, 16 Oct 2026 16:48:28 +0200
Subject: [PATCH 5/7] Document BGEN migration under changelog deprecations

Clarify that BGEN reading and conversion are already removed, unlike the retained deprecated PLINK API, and point users to bio2zarr and legacy-store unpacking guidance.

Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
---
 docs/changelog.rst | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/docs/changelog.rst b/docs/changelog.rst
index cf764e3eb..923727779 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -30,6 +30,14 @@ Breaking changes
 Deprecations
 ~~~~~~~~~~~~
 
+- BGEN reading and conversion have moved out of sgkit. Use
+  `bio2zarr <https://github.com/sgkit-dev/bio2zarr>`_ for BGEN-to-Zarr conversion
+  and :func:`load_dataset` for analysis. Unlike the deprecated PLINK functions
+  below, ``read_bgen``, ``bgen_to_zarr`` and ``rechunk_bgen`` are already removed
+  in this release; see Breaking changes above and
+  :ref:`bgen_conversion_migration`. Only the dependency-free
+  :func:`sgkit.io.bgen.unpack_variables` helper remains for legacy packed stores.
+  (:pr:`1325`, :issue:`1331`, :issue:`1355`)
 - Functions for reading and writing plink are deprecated, please use the `bio2zarr <https://github.com/sgkit-dev/bio2zarr>`_
   and `vcztools <https://github.com/sgkit-dev/vcztools>`_ packages.
   (:user:`tomwhite`, :pr:`1324`, :issue:`1318`)

From 7c72e2ce7f4f79aace6e2c589b9dc7edf11b70b8 Mon Sep 17 00:00:00 2001
From: Julianus Pfeuffer <8102638+jpfeuffer@users.noreply.github.com>
Date: Fri, 16 Oct 2026 18:16:25 +0200
Subject: [PATCH 6/7] Remove redundant BGEN wheel smoke assertions

Restore the existing general wheel smoke script by removing the added BGEN export/dependency assertions and synthetic unpacking example, as requested. Leave established behavioral tests unchanged.

Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
---
 .github/scripts/test_sgkit.py | 23 -----------------------
 1 file changed, 23 deletions(-)

diff --git a/.github/scripts/test_sgkit.py b/.github/scripts/test_sgkit.py
index 2f62e7dd3..1ad14f2e2 100644
--- a/.github/scripts/test_sgkit.py
+++ b/.github/scripts/test_sgkit.py
@@ -1,28 +1,5 @@
-from importlib.metadata import metadata, requires
-
-import xarray as xr
-
 import sgkit as sg
-from sgkit.io import bgen
 
 if __name__ == "__main__":
     ds = sg.simulate_genotype_call_dataset(n_variant=100, n_sample=50, n_contig=23)
     print(ds)
-    assert bgen.__all__ == ["unpack_variables"]
-    assert "bgen" not in metadata("sgkit").get_all("Provides-Extra", [])
-    assert not any("cbgen" in requirement for requirement in requires("sgkit"))
-    packed = xr.Dataset(
-        {
-            "call_genotype_probability": (
-                ("variants", "samples", "genotypes"),
-                [[[0.25, 0.5]]],
-            ),
-            "call_genotype_probability_mask": (
-                ("variants", "samples"),
-                [[False]],
-            ),
-        }
-    )
-    unpacked = bgen.unpack_variables(packed)
-    assert unpacked.call_genotype_probability.values.tolist() == [[[0.25, 0.25, 0.5]]]
-    assert unpacked.call_dosage.item() == 1.25

From e014ffb9bdd5f902d393e955202f49fdc44fb56f Mon Sep 17 00:00:00 2001
From: Julianus Pfeuffer <8102638+jpfeuffer@users.noreply.github.com>
Date: Fri, 16 Oct 2026 20:43:10 +0200
Subject: [PATCH 7/7] Fix strict docs links and Zarr 3 legacy-store CI tests

Add the fsspec intersphinx inventory so StoreLike type annotations resolve FSMap. Use eager variable-length sample strings in the legacy packed-store fixture rather than unstable fixed-width UTF32 under Zarr format 3. Keep probability data chunked and warnings strict.

Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
---
 docs/conf.py                      |  1 +
 sgkit/tests/io/test_bgen_utils.py | 33 +++++++++++++++++--------------
 2 files changed, 19 insertions(+), 15 deletions(-)

diff --git a/docs/conf.py b/docs/conf.py
index 482d17157..eead605b9 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -134,6 +134,7 @@ def filter(self, record: pylogging.LogRecord) -> bool:
 
 intersphinx_mapping = dict(
     dask=("https://docs.dask.org/en/stable/", None),
+    fsspec=("https://filesystem-spec.readthedocs.io/en/latest/", None),
     xarray=("https://docs.xarray.dev/en/stable/", None),
     zarr=("https://zarr.readthedocs.io/en/stable", None),
     numpy=("https://numpy.org/doc/stable/", None),
diff --git a/sgkit/tests/io/test_bgen_utils.py b/sgkit/tests/io/test_bgen_utils.py
index fcdd4164b..7ca2c1fb3 100644
--- a/sgkit/tests/io/test_bgen_utils.py
+++ b/sgkit/tests/io/test_bgen_utils.py
@@ -79,21 +79,24 @@ def find_spec(self, fullname, path=None, target=None):
 
 @pytest.fixture
 def packed_dataset():
-    return xr.Dataset(
-        {
-            "call_genotype_probability": (
-                ("variants", "samples", "genotypes"),
-                [[[0.25, 0.5], [np.nan, np.nan]], [[0.0, 1.0], [0.0, 0.0]]],
-            ),
-            "call_genotype_probability_mask": (
-                ("variants", "samples"),
-                [[False, True], [False, False]],
-            ),
-            "variant_position": ("variants", [10, 20]),
-            "sample_id": ("samples", ["a", "b"]),
-        },
-        attrs={"source": "legacy packed BGEN store"},
-    ).chunk({"variants": 1, "samples": 1})
+    return (
+        xr.Dataset(
+            {
+                "call_genotype_probability": (
+                    ("variants", "samples", "genotypes"),
+                    [[[0.25, 0.5], [np.nan, np.nan]], [[0.0, 1.0], [0.0, 0.0]]],
+                ),
+                "call_genotype_probability_mask": (
+                    ("variants", "samples"),
+                    [[False, True], [False, False]],
+                ),
+                "variant_position": ("variants", [10, 20]),
+            },
+            attrs={"source": "legacy packed BGEN store"},
+        )
+        .chunk({"variants": 1, "samples": 1})
+        .assign(sample_id=("samples", np.array(["a", "b"], dtype=object)))
+    )
 
 
 @pytest.mark.parametrize("dtype", ["float32", "float64"])