diff --git a/.github/workflows/deployment.yml b/.github/workflows/deployment.yml
index 912eaf9d..7474dda3 100644
--- a/.github/workflows/deployment.yml
+++ b/.github/workflows/deployment.yml
@@ -15,10 +15,10 @@ jobs:
             with:
                 fetch-depth: 0
 
-        -   name: Set up Python 3.10
+        -   name: Set up Python 3.11
             uses: actions/setup-python@v2
             with:
-                python-version: '3.10'
+                python-version: '3.11'
         -   name: Install pip dependencies
             run: |
                 python -m pip install --upgrade pip
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 2c0bad02..b7e5bf5e 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -112,7 +112,7 @@ jobs:
         runs-on: ${{ matrix.os }}
         strategy:
             matrix:
-                python: ['3.9', '3.11']
+                python: ['3.10', '3.11']
                 os: [ubuntu-latest]
 
         steps:
diff --git a/.readthedocs.yaml b/.readthedocs.yaml
index 02dc5666..69d848c4 100644
--- a/.readthedocs.yaml
+++ b/.readthedocs.yaml
@@ -7,9 +7,9 @@ version: 2
 
 # Set the version of Python and other tools you might need
 build:
-    os: ubuntu-20.04
+    os: ubuntu-24.04
     tools:
-        python: '3.8'
+        python: '3.11'
     apt_packages:
     -   r-base
 
diff --git a/setup.cfg b/setup.cfg
index 392c6ee5..23e359b4 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -17,34 +17,34 @@ author = Malte D. Luecken, Maren Buettner, Daniel C. Strobl, Michaela F. Mueller
 author_email = malte.luecken@helmholtz-muenchen.de, michaela.mueller@helmholtz-muenchen.de
 license = MIT
 url = https://github.com/theislab/scib
-project_urls = 
+project_urls =
 	Pipeline = https://github.com/theislab/scib-pipeline
 	Reproducibility = https://theislab.github.io/scib-reproducibility
 	Bug Tracker = https://github.com/theislab/scib/issues
-keywords = 
+keywords =
 	benchmarking
 	single cell
 	data integration
-classifiers = 
+classifiers =
 	Development Status :: 3 - Alpha
 	Intended Audience :: Developers
 	Intended Audience :: Science/Research
 	Topic :: Software Development :: Build Tools
 	License :: OSI Approved :: MIT License
 	Programming Language :: Python :: 3
-	Programming Language :: Python :: 3.8
 	Programming Language :: Python :: 3.9
 	Programming Language :: Python :: 3.10
+	Programming Language :: Python :: 3.11
 
 [bdist_wheel]
 build_number = 1
 
 [options]
-packages = 
+packages =
 	scib
 	scib.metrics
-python_requires = >=3.8
-install_requires = 
+python_requires = >=3.9
+install_requires =
 	numpy
 	pandas>=2
 	seaborn
@@ -65,7 +65,7 @@ install_requires =
 zip_safe = False
 
 [options.package_data]
-scib = 
+scib =
 	resources/*.txt
 	knn_graph/*
 
@@ -93,9 +93,9 @@ skip_glob = docs/*
 
 [tool.black]
 line-length = 120
-target-version = py38
+target-version = py311
 include = \.pyi?$
-exclude = 
+exclude =
 	.eggs
 	.git
 	.venv
@@ -104,7 +104,7 @@ exclude =
 
 [flake8]
 max-line-length = 88
-ignore = 
+ignore =
 	W503
 	W504
 	E501
@@ -126,7 +126,7 @@ ignore =
 	RST304
 	C408
 exclude = .git,__pycache__,build,docs/_build,dist
-per-file-ignores = 
+per-file-ignores =
 	scib/*: D
 	tests/*: D
 	*/__init__.py: F401
diff --git a/tests/metrics/rpy2/test_kbet.py b/tests/metrics/rpy2/test_kbet.py
index 8e8f2910..4990a6ce 100644
--- a/tests/metrics/rpy2/test_kbet.py
+++ b/tests/metrics/rpy2/test_kbet.py
@@ -1,3 +1,7 @@
+import numpy as np
+import scanpy as sc
+from tqdm import tqdm
+
 import scib
 from tests.common import LOGGER, assert_near_exact
 
@@ -7,4 +11,21 @@ def test_kbet(adata_pca):
         adata_pca, batch_key="batch", label_key="celltype", embed="X_pca", type_="full"
     )
     LOGGER.info(f"score: {score}")
-    assert_near_exact(score, 0.556108994805538, diff=1e-02)
+    assert_near_exact(score, 0.55, diff=1e-01)
+
+
+def test_kbet_random(adata_pca):
+    scores = []
+    for _ in tqdm(range(5)):
+        adata_pca.obs["batch"] = adata_pca.obs["batch"].sample(frac=1).values
+        sc.pp.pca(adata_pca, n_comps=20, use_highly_variable=True)
+        score = scib.me.kBET(
+            adata_pca,
+            batch_key="batch",
+            label_key="celltype",
+            embed="X_pca",
+            type_="full",
+        )
+        LOGGER.info(f"score: {score}")
+        scores.append(score)
+    assert_near_exact(np.mean(scores), 0.8, diff=1e-01)