Merge branch 'main' into wilcoxon-refactor

Author: Intron7

.pre-commit-config.yaml

@@ -37,7 +37,7 @@ repos:
               docs/references.bib|
           )
 -   repo: https://github.com/pre-commit/mirrors-clang-format
-    rev: v22.1.4
+    rev: v22.1.5
     hooks:
     -   id: clang-format
         args: [--style=file, -i]

docs/basic.md

@@ -62,8 +62,8 @@ If you use rapids-singlecell, please cite:
 
 ## News
 
+* 30.04.26 [**v0.15.0 released!**](https://scverse.org/blog/2026-rsc-goes-nanobind/) This release ships precompiled CUDA kernels via [nanobind](https://github.com/wjakob/nanobind) — no CUDA toolkit needed at install time. Prebuilt wheels for x86_64 and aarch64 support CUDA 12 and 13, covering Turing through Blackwell GPUs. Install with `pip install rapids-singlecell-cu13` (or `-cu12`). See the [installation guide](installation.md) for details.
 * 04.03.26 **rapids-singlecell is now on arXiv!** Check out our preprint: [GPU-accelerated single-cell analysis at scale with rapids-singlecell](https://doi.org/10.48550/arXiv.2603.02402)
-* 19.02.26 **v0.15.0 pre-release available!** This release ships precompiled CUDA kernels via [nanobind](https://github.com/wjakob/nanobind) — no CUDA toolkit needed at install time. Prebuilt wheels for x86_64 and aarch64 support CUDA 12 and 13, covering Turing through Blackwell GPUs. Install with `pip install --pre rapids-singlecell-cu13` (or `-cu12`) and help us test! See the [installation guide](installation.md) for details.
 * 01.07.25 *rapids-singlecell* is now an [scverse® core package](https://scverse.org/blog/2025-core-expansion/)
 * 12.06.25 *rapids-singlecell* was highlighted in an other NVIDIA [technical blog post](https://developer.nvidia.com/blog/driving-toward-billion-cell-analysis-and-biological-breakthroughs-with-rapids-singlecell/)
 * 07.08.23 *rapids-singlecell* is now part of scverse® ecosystem.

docs/conf.py

@@ -149,6 +149,7 @@
     "repository_branch": os.environ.get("READTHEDOCS_GIT_IDENTIFIER", "main"),
     "use_repository_button": True,
     "navigation_with_keys": False,
+    "show_toc_level": 2,
 }
 html_show_sphinx = False
 html_logo = "_static/logo_RTD.svg"

docs/installation.md

@@ -26,22 +26,8 @@ mamba env create -f conda/rsc_rapids_26.04_cuda12.yml
 RAPIDS currently doesn't support `channel_priority: strict`; use `channel_priority: flexible` instead
 ```
 
-```{warning}
-The conda environment files on the `main` branch reference the new `rapids-singlecell-cu12`/`-cu13` wheel names, which are currently only available as pre-release.
-Until 0.15.0 is released, use the environment files from the [v0.14.1 tag](https://github.com/scverse/rapids_singlecell/tree/v0.14.1/conda) instead, or add `--pre` to the pip line manually.
-```
-
 ## PyPI
 
-```{note}
-**Pre-release testing:** Version 0.15.0 is currently in pre-release. We'd love for you to test it
-and report any issues! Install the latest release candidate with:
-
-    pip install --pre rapids-singlecell-cu13  # or rapids-singlecell-cu12
-
-Please report any problems on [GitHub Issues](https://github.com/scverse/rapids_singlecell/issues).
-```
-
 Starting with version 0.15.0, *rapids-singlecell* ships precompiled CUDA kernels via nanobind.
 Prebuilt wheels are available for **x86_64** and **aarch64** Linux for both CUDA 12 and CUDA 13.
 

docs/notebooks/01_basic_workflow.ipynb

@@ -0,0 +1 @@
+../../notebooks/01_basic_workflow.ipynb

docs/notebooks/01_demo_gpu.ipynb

@@ -0,0 +1 @@
+../../notebooks/02_pearson_residuals.ipynb

docs/notebooks/02_decoupler.ipynb

@@ -0,0 +1 @@
+../../notebooks/03_decoupler.ipynb