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Backport PR #2901: Doc submodule (#2962)
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Co-authored-by: Isaac Virshup <[email protected]>
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meeseeksmachine and ivirshup authored Mar 26, 2024
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3 changes: 3 additions & 0 deletions .gitmodules
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[submodule "notebooks"]
path = notebooks
url = https://github.com/scverse/scanpy-tutorials/
2 changes: 2 additions & 0 deletions .readthedocs.yml
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version: 2
submodules:
include: all
build:
os: ubuntu-20.04
tools:
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142 changes: 0 additions & 142 deletions docs/_tutorials.md

This file was deleted.

2 changes: 1 addition & 1 deletion docs/api/plotting.md
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The plotting module {mod}`scanpy.pl` largely parallels the `tl.*` and a few of the `pp.*` functions.
For most tools and for some preprocessing functions, you'll find a plotting function with the same name.

See {doc}`tutorials:plotting/core` for an overview of how to use these functions.
See {doc}`/tutorials/plotting/core` for an overview of how to use these functions.

```{note}
See the {ref}`settings` section for all important plotting configurations.
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# -- General configuration ------------------------------------------------


nitpicky = True # Warn about broken links. This is here for a reason: Do not change.
needs_sphinx = "4.0" # Nicer param docs
suppress_warnings = [
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release = version

# Bibliography settings
bibtex_bibfiles = ["references.bib"]
bibtex_reference_style = "author_year"


# default settings
templates_path = ["_templates"]
master_doc = "index"
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"sphinx.ext.napoleon",
"sphinx.ext.autosummary",
"sphinx.ext.extlinks",
"sphinxcontrib.bibtex",
"matplotlib.sphinxext.plot_directive",
"sphinx_autodoc_typehints", # needs to be after napoleon
"git_ref", # needs to be before scanpydoc.rtd_github_links
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"html_image",
"html_admonition",
]
myst_url_schemes = ("http", "https", "mailto")
myst_url_schemes = ("http", "https", "mailto", "ftp")
nb_output_stderr = "remove"
nb_execution_mode = "off"
nb_merge_streams = True
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scipy=("https://docs.scipy.org/doc/scipy/", None),
seaborn=("https://seaborn.pydata.org/", None),
sklearn=("https://scikit-learn.org/stable/", None),
tutorials=("https://scanpy-tutorials.readthedocs.io/en/latest/", None),
)


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2 changes: 1 addition & 1 deletion docs/extensions/cite.py
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def setup(app: Sphinx):
app.add_role("cite", cite_role, override=True)
app.add_role("cite-hack", cite_role, override=True)
7 changes: 7 additions & 0 deletions docs/how-to/index.md
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# How to

This section contains short examples on how to perform specific tasks with scanpy.

```{toctree}
knn-transformers
```
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10 changes: 6 additions & 4 deletions docs/index.md
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:::

:::{grid-item-card} Tutorials {octicon}`play;1em;`
:link: _tutorials
:link: tutorials/index
:link-type: doc

The tutorials walk you through real-world applications of scanpy.
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::::

**Other resources**

* Follow changes in the {ref}`release notes <release-notes>`.
* Find tools that harmonize well with anndata & Scanpy via the {doc}`external API <external/index>` and the {doc}`ecosystem page <ecosystem>`.
* Find tools that harmonize well with anndata & Scanpy at [scverse.org/packages/](https://scverse.org/packages/)
* Check out our {ref}`contribution guide <contribution-guide>` for development practices.
* Consider citing [Genome Biology (2018)] along with original {doc}`references <references>`.

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:hidden: true
:maxdepth: 1
_tutorials
usage-principles
installation
tutorials/index
usage-principles
how-to/index
api/index
external/index
ecosystem
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2 changes: 1 addition & 1 deletion docs/installation.md
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```

The extra `[leiden]` installs two packages that are needed for popular
parts of scanpy but aren't requirements: [igraph] {cite}`Csardi06` and [leiden] {cite}`Traag18`.
parts of scanpy but aren't requirements: [igraph] {cite-hack}`Csardi06` and [leiden] {cite-hack}`Traag18`.

(dev-install-instructions)=

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6 changes: 5 additions & 1 deletion docs/news.md
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```

### `rapids-singlecell` brings scanpy to the GPU! {small}`2024-03-18`

{doc}`rapids-singlecell <rapids_singlecell:index>` by Severin Dicks provides a scanpy-like API with accelerated operations implemented on GPU.

### Scanpy hits 100 contributors! {small}`2022-03-31`

[100 people have contributed to Scanpy's source code!](https://github.com/scverse/scanpy/graphs/contributors)
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### Science “Breakthrough of the Year 2018” {small}`2018-12-01`

The Science “Breakthrough of the Year 2018”, [Development cell by cell](https://vis.sciencemag.org/breakthrough2018/finalists/#cell-development), mentions the first application of PAGA {cite}`Plass18` among 5 papers.
The Science “Breakthrough of the Year 2018”, [Development cell by cell](https://vis.sciencemag.org/breakthrough2018/finalists/#cell-development), mentions the first application of PAGA {cite-hack}`Plass18` among 5 papers.

[32 projects]: https://chanzuckerberg.com/eoss/proposals/
[essential open source software for science]: https://chanzuckerberg.com/newsroom/chan-zuckerberg-initiative-awards-5-million-for-open-source-software-projects-essential-to-science/
100 changes: 100 additions & 0 deletions docs/references.bib
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@article{Wolf2018,
author = {Wolf, F. Alexander
and Angerer, Philipp
and Theis, Fabian J.},
title = {SCANPY: large-scale single-cell gene expression data analysis},
journal = {Genome Biology},
year = {2018},
month = {Feb},
day = {06},
volume = {19},
number = {1},
pages = {15},
abstract = {Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells (https://github.com/theislab/Scanpy). Along with Scanpy, we present AnnData, a generic class for handling annotated data matrices (https://github.com/theislab/anndata).},
issn = {1474-760X},
doi = {10.1186/s13059-017-1382-0},
url = {https://doi.org/10.1186/s13059-017-1382-0}
}
@inproceedings{luecken2021,
author = {Luecken, Malte and Burkhardt, Daniel and Cannoodt, Robrecht and Lance, Christopher and Agrawal, Aditi and Aliee, Hananeh and Chen, Ann and Deconinck, Louise and Detweiler, Angela and Granados, Alejandro and Huynh, Shelly and Isacco, Laura and Kim, Yang and Klein, Dominik and DE KUMAR, BONY and Kuppasani, Sunil and Lickert, Heiko and McGeever, Aaron and Melgarejo, Joaquin and Mekonen, Honey and Morri, Maurizio and M\"{u}ller, Michaela and Neff, Norma and Paul, Sheryl and Rieck, Bastian and Schneider, Kaylie and Steelman, Scott and Sterr, Michael and Treacy, Daniel and Tong, Alexander and Villani, Alexandra-Chloe and Wang, Guilin and Yan, Jia and Zhang, Ce and Pisco, Angela and Krishnaswamy, Smita and Theis, Fabian and Bloom, Jonathan M},
booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks},
editor = {J. Vanschoren and S. Yeung},
pages = {},
publisher = {Curran},
title = {A sandbox for prediction and integration of DNA, RNA, and proteins in single cells},
url = {https://datasets-benchmarks-proceedings.neurips.cc/paper_files/paper/2021/file/158f3069a435b314a80bdcb024f8e422-Paper-round2.pdf},
volume = {1},
year = {2021}
}
@article{McCarthy2017,
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journal = {Bioinformatics}
}
@article{Wolock2019,
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@article{Zheng2017,
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@article{stuart2019comprehensive,
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