docs: switch to scverse.org domain

CITATION.cff

@@ -9,7 +9,7 @@ abstract: >-
 type: software
 license: Apache-2.0
 repository-code: https://github.com/scverse/pertpy
-url: https://pertpy.readthedocs.io
+url: https://pertpy.scverse.org/
 keywords:
   - single-cell
   - perturbation

README.md

@@ -3,7 +3,7 @@
 [![License](https://img.shields.io/github/license/scverse/pertpy)](https://opensource.org/licenses/Apache2.0)
 [![PyPI](https://img.shields.io/pypi/v/pertpy.svg)](https://pypi.org/project/pertpy/)
 [![Python Version](https://img.shields.io/pypi/pyversions/pertpy)](https://pypi.org/project/pertpy)
-[![Read the Docs](https://img.shields.io/readthedocs/pertpy/latest.svg?label=Read%20the%20Docs)](https://pertpy.readthedocs.io/)
+[![Read the Docs](https://img.shields.io/readthedocs/pertpy/latest.svg?label=Read%20the%20Docs)](https://pertpy.scverse.org/)
 [![Test](https://github.com/scverse/pertpy/actions/workflows/test.yml/badge.svg)](https://github.com/scverse/pertpy/actions/workflows/test.yml)
 [![PyPI](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
 
@@ -18,7 +18,7 @@ Please read our associated manuscript ["Pertpy: an end-to-end framework for pert
 
 ## Documentation
 
-Please read the [documentation](https://pertpy.readthedocs.io/en/latest) for installation instructions, tutorials, use cases, and more.
+Please read the [documentation](https://pertpy.scverse.org/) for installation instructions, tutorials, use cases, and more.
 
 ## Installation
 
@@ -99,7 +99,7 @@ pip install rpy2
 
 [pip]: https://pip.pypa.io/
 [pypi]: https://pypi.org/
-[api]: https://pertpy.readthedocs.io/en/latest/api.html
+[api]: https://pertpy.scverse.org/page/api.html
 [conda-forge]: https://anaconda.org/conda-forge/pertpy
 [//]: # "numfocus-fiscal-sponsor-attribution"
 

docs/api/preprocessing_index.md

@@ -39,4 +39,4 @@ ga.assign_by_threshold(gdo, 5, layer="counts", output_layer="assigned_guides")
 ga.plot_heatmap(gdo, layer="assigned_guides")
 ```
 
-See [guide assignment tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/guide_rna_assignment.html).
+See {doc}`/tutorials/notebooks/guide_rna_assignment` tutorial.

docs/api/tools_index.md

@@ -62,7 +62,7 @@ EdgeR
     Fitted        yes
 ```
 
-See [differential gene expression tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/differential_gene_expression.html).
+See {doc}`/tutorials/notebooks/differential_gene_expression` tutorial.
 
 ## Pooled CRISPR screens
 
@@ -99,7 +99,7 @@ ms.lda(adata=mdata["rna"], labels="gene_target", layer="X_pert", control="NT")
 ms.plot_lda(adata=mdata["rna"], control="NT")
 ```
 
-See [perturbation efficacy tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/perturbation_efficacy.html).
+See {doc}`/tutorials/notebooks/perturbation_efficacy` tutorial.
 
 ### Perturbation scoring - Mixscale
 
@@ -126,7 +126,7 @@ ms.perturbation_signature(mdata["rna"], "perturbation", "NT", split_by="replicat
 ms.mixscale(mdata["rna"], "gene_target", "NT", layer="X_pert")
 ```
 
-See [perturbation efficacy tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/perturbation_efficacy.html).
+See {doc}`/tutorials/notebooks/perturbation_efficacy` tutorial.
 
 ## Compositional analysis
 
@@ -182,7 +182,7 @@ milo.group_nhoods(mdata)
 milo.annotate_cells_from_nhoods(mdata)
 ```
 
-See [milo tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/milo.html).
+See {doc}`/tutorials/notebooks/milo` tutorial.
 
 ### With labeled groups - scCODA and tascCODA
 
@@ -232,7 +232,7 @@ sccoda.summary(sccoda_data, modality_key="coda_salm")
 sccoda.plot_effects_barplot(sccoda_data, modality_key="coda_salm", parameter="Final Parameter")
 ```
 
-See [sccoda tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/sccoda.html), [extended sccoda tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/sccoda_extended.html) and [tasccoda tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/tasccoda.html).
+See {doc}`/tutorials/notebooks/sccoda`, {doc}`/tutorials/notebooks/sccoda_extended`, and {doc}`/tutorials/notebooks/tasccoda` tutorials.
 
 ## Multicellular and gene programs
 
@@ -285,7 +285,7 @@ dl.get_program_genes(adata, program="MCP1", celltype="CD8+ IELs")
 dl.test_phenotype_association(adata, condition_key="path_str")
 ```
 
-See [DIALOGUE tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/dialogue.html).
+See {doc}`/tutorials/notebooks/dialogue` tutorial.
 
 ### Enrichment
 
@@ -361,7 +361,7 @@ A high reversal score is a hypothesis for follow-up, not evidence of therapeutic
 In particular, a perturbation can score highly by suppressing a compensatory or protective stress response.
 Results should therefore be interpreted together with biological context and orthogonal phenotypic, viability, and toxicity measurements.
 
-See [enrichment tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/enrichment.html).
+See {doc}`/tutorials/notebooks/enrichment` tutorial.
 
 ## Distances and permutation tests
 
@@ -399,8 +399,7 @@ etest = pt.tl.DistanceTest("edistance", n_perms=1000, obsm_key="X_pca")
 tab = etest(adata, groupby="perturbation", contrast="control")
 ```
 
-See [distance tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/distances.html)
-and [distance tests tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/distance_tests.html).
+See {doc}`/tutorials/notebooks/distances` and {doc}`/tutorials/notebooks/distance_tests` tutorials.
 
 ## Response prediction
 
@@ -431,7 +430,7 @@ adata, results = ag.predict(adata)
 results["summary_metrics"]
 ```
 
-See [augur tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/augur.html).
+See {doc}`/tutorials/notebooks/augur` tutorial.
 
 ```{eval-rst}
 .. autosummary::
@@ -472,7 +471,7 @@ pred, delta = scgen.predict(ctrl_key="control", stim_key="stimulated", celltype_
 pred.obs["condition"] = "pred"
 ```
 
-See [scgen tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/scgen_perturbation_prediction.html).
+See {doc}`/tutorials/notebooks/scgen_perturbation_prediction` tutorial.
 
 ### Causal perturbation analysis with CINEMA-OT
 
@@ -510,7 +509,7 @@ de = model.causaleffect(
 )
 ```
 
-See [CINEMA-OT tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/cinemaot.html).
+See {doc}`/tutorials/notebooks/cinemaot` tutorial.
 
 ## Perturbation space
 
@@ -552,7 +551,7 @@ ds_adata = ds.compute(mdata["rna"], target_col="gene_target", metric="edistance"
 similar = ds.nearest_perturbations(ds_adata, "IFNGR2", target_col="gene_target")
 ```
 
-See [perturbation space tutorial](https://pertpy.readthedocs.io/en/latest/tutorials/notebooks/perturbation_space.html).
+See {doc}`/tutorials/notebooks/perturbation_space` tutorial.
 
 ### Dose-response curve fitting
 

docs/conf.py

@@ -118,15 +118,15 @@
 add_module_names = False
 autodoc_mock_imports = ["ete4"]
 intersphinx_mapping = {
-    "anndata": ("https://anndata.readthedocs.io/en/stable/", None),
+    "anndata": ("https://anndata.scverse.org/en/stable/", None),
     "decoupler": ("https://decoupler.readthedocs.io/en/latest/", None),
     "mudata": ("https://mudata.readthedocs.io/stable/", None),
     "matplotlib": ("https://matplotlib.org/stable/", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
     "pandas": ("https://pandas.pydata.org/docs/", None),
     "python": ("https://docs.python.org/3", None),
     "scipy": ("https://docs.scipy.org/doc/scipy/", None),
-    "scanpy": ("https://scanpy.readthedocs.io/en/stable/", None),
+    "scanpy": ("https://scanpy.scverse.org/en/stable/", None),
     "seaborn": ("https://seaborn.pydata.org/", None),
     "pyro": ("https://docs.pyro.ai/en/stable/", None),
     "pymde": ("https://pymde.org/", None),

docs/contributing.md

@@ -5,11 +5,10 @@ We assume that you are already familiar with git and with making pull requests o
 
 For more extensive tutorials, that also cover the absolute basics,
 please refer to other resources such as the [pyopensci tutorials][],
-the [scientific Python tutorials][], or the [scanpy developer guide][].
+the [scientific Python tutorials][], or the {doc}`scanpy developer guide <scanpy:dev/index>`.
 
 [pyopensci tutorials]: https://www.pyopensci.org/learn.html
 [scientific Python tutorials]: https://learn.scientific-python.org/development/tutorials/
-[scanpy developer guide]: https://scanpy.readthedocs.io/en/latest/dev/index.html
 
 :::{tip} The *hatch* project manager
 

docs/llms.txt

@@ -11,47 +11,47 @@ Every page listed below is also available as Markdown by requesting it with the
 
 ## Start here
 
-- [Installation](https://pertpy.readthedocs.io/en/stable/installation.html): pip and conda-forge installation, including the `jax`, `de`, `tcoda` and `scgen` extras that individual tools require.
-- [API reference](https://pertpy.readthedocs.io/en/stable/api.html): entry point to all four modules.
-- [Tutorials](https://pertpy.readthedocs.io/en/stable/tutorials.html): executable notebooks for every tool.
-- [Use cases](https://pertpy.readthedocs.io/en/stable/usecases.html): end-to-end reanalyses of published perturbation studies.
+- [Installation](https://pertpy.scverse.org/page/installation.html): pip and conda-forge installation, including the `jax`, `de`, `tcoda` and `scgen` extras that individual tools require.
+- [API reference](https://pertpy.scverse.org/page/api.html): entry point to all four modules.
+- [Tutorials](https://pertpy.scverse.org/page/tutorials.html): executable notebooks for every tool.
+- [Use cases](https://pertpy.scverse.org/page/usecases.html): end-to-end reanalyses of published perturbation studies.
 
 ## Tools by task
 
-- [Differential gene expression](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#differential-gene-expression): `pt.tl.PyDESeq2`, `pt.tl.EdgeR`, `pt.tl.WilcoxonTest`, `pt.tl.TTest`, `pt.tl.PermutationTest` and `pt.tl.Statsmodels` behind one interface that supports complex designs and contrasts.
-- [Perturbation assignment and efficacy](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#pooled-crispr-screens): `pt.tl.Mixscape` for binary perturbed/non-perturbed calls and `pt.tl.Mixscale` for continuous perturbation scores in pooled CRISPR screens.
-- [Differential abundance without labeled groups](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#compositional-analysis): `pt.tl.Milo` tests differential abundance on k-nearest-neighbor graph neighborhoods.
-- [Compositional analysis with labeled groups](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#compositional-analysis): `pt.tl.Sccoda` and `pt.tl.Tasccoda` model cell type composition with Bayesian hierarchical models.
-- [Multicellular programs](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#multicellular-programs-dialogue): `pt.tl.Dialogue` identifies latent programs coordinated across cell types.
-- [Enrichment](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#enrichment): `pt.tl.Enrichment` scores pathway and drug target gene sets, including drug2cell.
-- [Perturbation distances and permutation tests](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#distances-and-permutation-tests): `pt.tl.Distance` computes metrics such as edistance, MMD and Wasserstein between perturbation groups, `pt.tl.DistanceTest` turns them into permutation tests.
-- [Perturbation spaces](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#perturbation-space): `pt.tl.PseudobulkSpace`, `pt.tl.CentroidSpace`, `pt.tl.DistanceSpace`, `pt.tl.EmbeddingSpace` and the classifier and clustering spaces summarize all cells of a perturbation into one observation.
-- [Cell type prioritization](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#rank-perturbations-augur): `pt.tl.Augur` ranks cell types by how strongly they respond to a perturbation.
-- [Response prediction](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#gene-expression-prediction-with-scgen): `pt.tl.Scgen` predicts cell-type-specific responses to a perturbation.
-- [Causal effect analysis](https://pertpy.readthedocs.io/en/stable/api/tools_index.html#causal-perturbation-analysis-with-cinema-ot): `pt.tl.Cinemaot` separates confounding variation from perturbation effects to obtain counterfactual cell pairs.
+- [Differential gene expression](https://pertpy.scverse.org/page/api/tools_index.html#differential-gene-expression): `pt.tl.PyDESeq2`, `pt.tl.EdgeR`, `pt.tl.WilcoxonTest`, `pt.tl.TTest`, `pt.tl.PermutationTest` and `pt.tl.Statsmodels` behind one interface that supports complex designs and contrasts.
+- [Perturbation assignment and efficacy](https://pertpy.scverse.org/page/api/tools_index.html#pooled-crispr-screens): `pt.tl.Mixscape` for binary perturbed/non-perturbed calls and `pt.tl.Mixscale` for continuous perturbation scores in pooled CRISPR screens.
+- [Differential abundance without labeled groups](https://pertpy.scverse.org/page/api/tools_index.html#compositional-analysis): `pt.tl.Milo` tests differential abundance on k-nearest-neighbor graph neighborhoods.
+- [Compositional analysis with labeled groups](https://pertpy.scverse.org/page/api/tools_index.html#compositional-analysis): `pt.tl.Sccoda` and `pt.tl.Tasccoda` model cell type composition with Bayesian hierarchical models.
+- [Multicellular programs](https://pertpy.scverse.org/page/api/tools_index.html#multicellular-programs-dialogue): `pt.tl.Dialogue` identifies latent programs coordinated across cell types.
+- [Enrichment](https://pertpy.scverse.org/page/api/tools_index.html#enrichment): `pt.tl.Enrichment` scores pathway and drug target gene sets, including drug2cell.
+- [Perturbation distances and permutation tests](https://pertpy.scverse.org/page/api/tools_index.html#distances-and-permutation-tests): `pt.tl.Distance` computes metrics such as edistance, MMD and Wasserstein between perturbation groups, `pt.tl.DistanceTest` turns them into permutation tests.
+- [Perturbation spaces](https://pertpy.scverse.org/page/api/tools_index.html#perturbation-space): `pt.tl.PseudobulkSpace`, `pt.tl.CentroidSpace`, `pt.tl.DistanceSpace`, `pt.tl.EmbeddingSpace` and the classifier and clustering spaces summarize all cells of a perturbation into one observation.
+- [Cell type prioritization](https://pertpy.scverse.org/page/api/tools_index.html#rank-perturbations-augur): `pt.tl.Augur` ranks cell types by how strongly they respond to a perturbation.
+- [Response prediction](https://pertpy.scverse.org/page/api/tools_index.html#gene-expression-prediction-with-scgen): `pt.tl.Scgen` predicts cell-type-specific responses to a perturbation.
+- [Causal effect analysis](https://pertpy.scverse.org/page/api/tools_index.html#causal-perturbation-analysis-with-cinema-ot): `pt.tl.Cinemaot` separates confounding variation from perturbation effects to obtain counterfactual cell pairs.
 
 ## Data and metadata
 
-- [Datasets](https://pertpy.readthedocs.io/en/stable/api/datasets_index.html): `pt.dt` downloads harmonized perturbation datasets such as `norman_2019`, `papalexi_2021`, `replogle_2022_k562_essential` and `srivatsan_2020_sciplex3`.
-- [Preprocessing](https://pertpy.readthedocs.io/en/stable/api/preprocessing_index.html): guide RNA assignment for pooled CRISPR screens.
-- [Metadata annotation](https://pertpy.readthedocs.io/en/stable/api/metadata_index.html): `pt.md.CellLine`, `pt.md.Compound`, `pt.md.Drug` and `pt.md.Moa` annotate cell lines, compounds and mechanisms of action from public databases.
+- [Datasets](https://pertpy.scverse.org/page/api/datasets_index.html): `pt.dt` downloads harmonized perturbation datasets such as `norman_2019`, `papalexi_2021`, `replogle_2022_k562_essential` and `srivatsan_2020_sciplex3`.
+- [Preprocessing](https://pertpy.scverse.org/page/api/preprocessing_index.html): guide RNA assignment for pooled CRISPR screens.
+- [Metadata annotation](https://pertpy.scverse.org/page/api/metadata_index.html): `pt.md.CellLine`, `pt.md.Compound`, `pt.md.Drug` and `pt.md.Moa` annotate cell lines, compounds and mechanisms of action from public databases.
 
 ## Tutorials
 
-- [Guide RNA assignment](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/guide_rna_assignment.html)
-- [Perturbation efficacy with Mixscape and Mixscale](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/perturbation_efficacy.html)
-- [Differential gene expression](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/differential_gene_expression.html)
-- [Differential abundance with Milo](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/milo.html)
-- [Compositional analysis with scCODA](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/sccoda.html)
-- [Perturbation distances](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/distances.html)
-- [Perturbation spaces](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/perturbation_space.html)
-- [Cell type prioritization with Augur](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/augur.html)
-- [Metadata annotation](https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/metadata_annotation.html)
+- [Guide RNA assignment](https://pertpy.scverse.org/page/tutorials/notebooks/guide_rna_assignment.html)
+- [Perturbation efficacy with Mixscape and Mixscale](https://pertpy.scverse.org/page/tutorials/notebooks/perturbation_efficacy.html)
+- [Differential gene expression](https://pertpy.scverse.org/page/tutorials/notebooks/differential_gene_expression.html)
+- [Differential abundance with Milo](https://pertpy.scverse.org/page/tutorials/notebooks/milo.html)
+- [Compositional analysis with scCODA](https://pertpy.scverse.org/page/tutorials/notebooks/sccoda.html)
+- [Perturbation distances](https://pertpy.scverse.org/page/tutorials/notebooks/distances.html)
+- [Perturbation spaces](https://pertpy.scverse.org/page/tutorials/notebooks/perturbation_space.html)
+- [Cell type prioritization with Augur](https://pertpy.scverse.org/page/tutorials/notebooks/augur.html)
+- [Metadata annotation](https://pertpy.scverse.org/page/tutorials/notebooks/metadata_annotation.html)
 
 ## Project
 
 - [Source code](https://github.com/scverse/pertpy)
 - [Publication](https://doi.org/10.1038/s41592-025-02909-7): Heumos et al., Pertpy: an end-to-end framework for perturbation analysis, Nature Methods 2025.
-- [Changelog](https://pertpy.readthedocs.io/en/stable/changelog.html)
-- [Contributing](https://pertpy.readthedocs.io/en/stable/contributing.html)
+- [Changelog](https://pertpy.scverse.org/page/changelog.html)
+- [Contributing](https://pertpy.scverse.org/page/contributing.html)
 - [Forum](https://discourse.scverse.org/c/ecosystem/pertpy/46)

pyproject.toml

@@ -25,11 +25,11 @@ authors = [
 maintainers = [
     {name = "Lukas Heumos", email = "lukas.heumos@posteo.net"},
 ]
-urls.Documentation = "https://pertpy.readthedocs.io"
+urls.Documentation = "https://pertpy.scverse.org/"
 urls.Source = "https://github.com/scverse/pertpy"
 urls.Home-page = "https://github.com/scverse/pertpy"
 urls.Issues = "https://github.com/scverse/pertpy/issues"
-urls.Changelog = "https://pertpy.readthedocs.io/en/stable/changelog.html"
+urls.Changelog = "https://pertpy.scverse.org/page/changelog.html"
 urls.Forum = "https://discourse.scverse.org/c/ecosystem/pertpy/46"
 urls.Publication = "https://doi.org/10.1038/s41592-025-02909-7"