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* Update docstrings

* Update `README.md`

* Update `api.rst`

Adds VELOVI and metabolic labeling inference.

* Update `installation.rst`

* Update `index.rst`
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100 changes: 67 additions & 33 deletions README.md
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Expand Up @@ -13,16 +13,13 @@

<img src="https://user-images.githubusercontent.com/31883718/67709134-a0989480-f9bd-11e9-8ae6-f6391f5d95a0.png" width="400px" align="left">

**scVelo** is a scalable toolkit for RNA velocity analysis in single cells, based on
[Bergen et al. (Nature Biotech, 2020](https://doi.org/10.1038/s41587-020-0591-3).

RNA velocity enables the recovery of directed dynamic information by leveraging splicing kinetics.
scVelo generalizes the concept of RNA velocity
[La Manno et al., Nature, 2018](https://doi.org/10.1038/s41586-018-0414-6>)
by relaxing previously made assumptions with a stochastic and a dynamical model that solves the full
transcriptional dynamics. It thereby adapts RNA velocity to widely varying specifications such as non-stationary populations.

scVelo is compatible with scanpy\_ and hosts efficient implementations of all RNA velocity models.
**scVelo** is a scalable toolkit for RNA velocity analysis in single cells; RNA velocity
enables the recovery of directed dynamic information by leveraging splicing kinetics
<sup>[1](https://doi.org/10.1038/s41586-018-0414-6)</sup>. scVelo collects different
methods for inferring RNA velocity using an expectation-maximization framework
<sup>[2](https://doi.org/10.1038/s41587-020-0591-3)</sup>, deep generative modeling
<sup>[3](https://doi.org/10.1038/s41592-023-01994-w)</sup>,
or metabolically labeled transcripts<sup>[4](https://doi.org/10.1101/2023.07.19.549685)</sup>.

## scVelo's key applications

Expand All @@ -32,35 +29,72 @@ scVelo is compatible with scanpy\_ and hosts efficient implementations of all RN
- estimate reaction rates of transcription, splicing and degradation.
- use statistical tests, e.g., to detect different kinetics regimes.

scVelo has, for instance, recently been used to study immune response in COVID-19
patients and dynamic processes in human lung regeneration. Find out more in this list of
[application examples](https://scholar.google.com/scholar?cites=18195185735875895912).

## Latest news

- Aug/2021: [Perspectives paper out in MSB](https://doi.org/10.15252/msb.202110282)
- Feb/2021: scVelo goes multi-core
- Dec/2020: Cover of [Nature Biotechnology](https://www.nature.com/nbt/volumes/38)
- Nov/2020: Talk at [Single Cell Biology](https://coursesandconferences.wellcomegenomecampus.org/our-events/single-cell-biology-2020/)
- Oct/2020: [Helmholtz Best Paper Award](https://twitter.com/ICBmunich/status/1318611467722199041)
- Oct/2020: Map cell fates with [CellRank](https://cellrank.org)
- Sep/2020: Talk at [Single Cell Omics](https://twitter.com/fabian_theis/status/1305621028056465412)
- Aug/2020: [scVelo out in Nature Biotech](https://www.helmholtz-muenchen.de/en/aktuelles/latest-news/press-information-news/article/48658/index.html)

## References

[La Manno _et al._ (2018), RNA velocity of single cells, Nature](https://doi.org/10.1038/s41586-018-0414-6).

[Bergen _et al._ (2020), Generalizing RNA velocity to transient cell states through dynamical modeling, Nature Biotech](https://doi.org/10.1038/s41587-020-0591-3).

[Bergen _et al._ (2021), RNA velocity - current challenges and future perspectives, Molecular Systems Biology](https://doi.org/10.15252/msb.202110282).
## Citing scVelo

If you include or rely on scVelo when publishing research, please adhere to the
following citation guide:

### EM and steady-state model

If you use the _EM_ (_dynamical_) or _steady-state model_, cite

```bibtex
@article{Bergen2020,
title = {Generalizing RNA velocity to transient cell states through dynamical modeling},
volume = {38},
ISSN = {1546-1696},
url = {http://dx.doi.org/10.1038/s41587-020-0591-3},
DOI = {10.1038/s41587-020-0591-3},
number = {12},
journal = {Nature Biotechnology},
publisher = {Springer Science and Business Media LLC},
author = {Bergen, Volker and Lange, Marius and Peidli, Stefan and Wolf, F. Alexander and Theis, Fabian J.},
year = {2020},
month = aug,
pages = {1408–1414}
}
```

### veloVI

If you use _veloVI_ (_VI model_), cite

```bibtex
@article{Gayoso2023,
title = {Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells},
ISSN = {1548-7105},
url = {http://dx.doi.org/10.1038/s41592-023-01994-w},
DOI = {10.1038/s41592-023-01994-w},
journal = {Nature Methods},
publisher = {Springer Science and Business Media LLC},
author = {Gayoso, Adam and Weiler, Philipp and Lotfollahi, Mohammad and Klein, Dominik and Hong, Justin and Streets, Aaron and Theis, Fabian J. and Yosef, Nir},
year = {2023},
month = sep
}
```

### RNA velocity inference through metabolic labeling information

If you use the implemented method for estimating RNA velocity from metabolic labeling
information, cite

```bibtex
@article{Weiler2023,
title = {Unified fate mapping in multiview single-cell data},
url = {http://dx.doi.org/10.1101/2023.07.19.549685},
DOI = {10.1101/2023.07.19.549685},
publisher = {Cold Spring Harbor Laboratory},
author = {Weiler, Philipp and Lange, Marius and Klein, Michal and Pe’er, Dana and Theis, Fabian J.},
year = {2023},
month = jul
}
```

## Support

Found a bug or would like to see a feature implemented? Feel free to submit an
[issue](https://github.com/theislab/scvelo/issues/new/choose).
Have a question or would like to start a new discussion? Head over to
[GitHub discussions](https://github.com/theislab/scvelo/discussions).
In either case, you can also always send us an [email](mailto:mail@scvelo.org).
Your help to improve scVelo is highly appreciated.
For further information visit [scvelo.org](https://scvelo.org).
13 changes: 13 additions & 0 deletions docs/source/api.rst
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Expand Up @@ -76,6 +76,7 @@ Tools (tl)

tl.recover_dynamics
tl.differential_kinetic_test
tl.VELOVI

**Dynamical genes**

Expand Down Expand Up @@ -105,6 +106,18 @@ Tools (tl)
tl.velocity_confidence
tl.score_genes_cell_cycle

Inference from metabolic labeling information
---------

.. autosummary::
:toctree: .

inference.get_labeling_time_mask
inference.get_labeling_times
inference.get_n_neighbors
inference.get_obs_dist_argsort
inference.get_parameters


Plotting (pl)
-------------
Expand Down
110 changes: 65 additions & 45 deletions docs/source/index.rst
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Expand Up @@ -9,16 +9,12 @@ scVelo - RNA velocity generalized through dynamical modeling

.. include:: _key_contributors.rst

**scVelo** is a scalable toolkit for RNA velocity analysis in single cells, based on
`Bergen et al. (Nature Biotech, 2020) <https://doi.org/10.1038/s41587-020-0591-3>`_.

RNA velocity enables the recovery of directed dynamic information by leveraging splicing kinetics.
scVelo generalizes the concept of RNA velocity
(`La Manno et al., Nature, 2018 <https://doi.org/10.1038/s41586-018-0414-6>`_)
by relaxing previously made assumptions with a stochastic and a dynamical model that solves the full
transcriptional dynamics. It thereby adapts RNA velocity to widely varying specifications such as non-stationary populations.

scVelo is compatible with Scanpy_ and hosts efficient implementations of all RNA velocity models.
**scVelo** is a scalable toolkit for RNA velocity analysis in single cells; RNA velocity
enables the recovery of directed dynamic information by leveraging splicing kinetics
:cite:p:`LaManno18`. scVelo collects different
methods for inferring RNA velocity using an expectation-maximization framework
:cite:p:`Bergen20`, deep generative modeling :cite:p:`Gayoso2023`,
or metabolically labeled transcripts :cite:p:`Weiler2023`.

scVelo's key applications
^^^^^^^^^^^^^^^^^^^^^^^^^
Expand All @@ -28,40 +24,77 @@ scVelo's key applications
- estimate reaction rates of transcription, splicing and degradation.
- use statistical tests, e.g., to detect different kinetics regimes.

scVelo has, for instance, recently been used to study immune response in COVID-19
patients and dynamic processes in human lung regeneration. Find out more in this list of
`application examples <https://scholar.google.com/scholar?cites=18195185735875895912>`_.

Latest news
^^^^^^^^^^^
- Aug/2021: `Perspectives paper out in MSB <https://doi.org/10.15252/msb.202110282>`_
- Feb/2021: scVelo goes multi-core
- Dec/2020: Cover of `Nature Biotechnology <https://www.nature.com/nbt/volumes/38>`_
- Nov/2020: Talk at `Single Cell Biology <https://coursesandconferences.wellcomegenomecampus.org/our-events/single-cell-biology-2020/>`_
- Oct/2020: `Helmholtz Best Paper Award <https://twitter.com/ICBmunich/status/1318611467722199041>`_
- Oct/2020: Map cell fates with `CellRank <https://cellrank.org>`_
- Sep/2020: Talk at `Single Cell Omics <https://twitter.com/fabian_theis/status/1305621028056465412>`_
- Aug/2020: `scVelo out in Nature Biotech <https://www.helmholtz-muenchen.de/en/aktuelles/latest-news/press-information-news/article/48658/index.html>`_
Citing scVelo
^^^^^^^^^^^^^

If you include or rely on scVelo when publishing research, please adhere to the
following citation guide:

**EM and steady-state model**

If you use the *EM* (*dynamical*) or *steady-state model*, cite

.. code-block:: bibtex
@article{Bergen2020,
title = {Generalizing RNA velocity to transient cell states through dynamical modeling},
volume = {38},
ISSN = {1546-1696},
url = {http://dx.doi.org/10.1038/s41587-020-0591-3},
DOI = {10.1038/s41587-020-0591-3},
number = {12},
journal = {Nature Biotechnology},
publisher = {Springer Science and Business Media LLC},
author = {Bergen, Volker and Lange, Marius and Peidli, Stefan and Wolf, F. Alexander and Theis, Fabian J.},
year = {2020},
month = aug,
pages = {1408–1414}
}
**veloVI**

References
^^^^^^^^^^
La Manno *et al.* (2018), RNA velocity of single cells, `Nature <https://doi.org/10.1038/s41586-018-0414-6>`_.
If you use *veloVI* (*VI model*), cite

Bergen *et al.* (2020), Generalizing RNA velocity to transient cell states through dynamical modeling,
`Nature Biotech <https://doi.org/10.1038/s41587-020-0591-3>`_.
.. code-block:: bibtex
Bergen *et al.* (2021), RNA velocity - current challenges and future perspectives,
`Molecular Systems Biology <https://doi.org/10.15252/msb.202110282>`_.
@article{Gayoso2023,
title = {Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells},
ISSN = {1548-7105},
url = {http://dx.doi.org/10.1038/s41592-023-01994-w},
DOI = {10.1038/s41592-023-01994-w},
journal = {Nature Methods},
publisher = {Springer Science and Business Media LLC},
author = {Gayoso, Adam and Weiler, Philipp and Lotfollahi, Mohammad and Klein, Dominik and Hong, Justin and Streets, Aaron and Theis, Fabian J. and Yosef, Nir},
year = {2023},
month = sep
}
**RNA velocity inference through metabolic labeling information**

If you use the implemented method for estimating RNA velocity from metabolic labeling
information, cite

.. code-block:: bibtex
@article{Weiler2023,
title = {Unified fate mapping in multiview single-cell data},
url = {http://dx.doi.org/10.1101/2023.07.19.549685},
DOI = {10.1101/2023.07.19.549685},
publisher = {Cold Spring Harbor Laboratory},
author = {Weiler, Philipp and Lange, Marius and Klein, Michal and Pe’er, Dana and Theis, Fabian J.},
year = {2023},
month = jul
}
Support
^^^^^^^
Found a bug or would like to see a feature implemented? Feel free to submit an
`issue <https://github.com/theislab/scvelo/issues/new/choose>`_.
Have a question or would like to start a new discussion? Head over to
`GitHub discussions <https://github.com/theislab/scvelo/discussions>`_.
In either case, you can also always send us an `email <mailto:mail@scvelo.org>`_.
Your help to improve scVelo is highly appreciated.
For further information visit `scvelo.org <https://scvelo.org>`_.


.. toctree::
Expand Down Expand Up @@ -103,25 +136,12 @@ For further information visit `scvelo.org <https://scvelo.org>`_.
.. |Docs| image:: https://readthedocs.org/projects/scvelo/badge/?version=latest
:target: https://scvelo.readthedocs.io

.. |travis| image:: https://travis-ci.org/theislab/scvelo.svg?branch=main
:target: https://travis-ci.org/theislab/scvelo

.. _Scanpy: https://scanpy.readthedocs.io

.. _calendly: https://calendly.com/scvelo

.. |br| raw:: html

<br/>

.. |meet| raw:: html

<!-- Calendly link widget begin -->
<link href="https://assets.calendly.com/assets/external/widget.css" rel="stylesheet">
<script src="https://assets.calendly.com/assets/external/widget.js" type="text/javascript"></script>
<a href="" onclick="Calendly.initPopupWidget({url: 'https://calendly.com/scvelo'});return false;">here</a>
<!-- Calendly link widget end -->

.. |dim| raw:: html

<span class="__dimensions_badge_embed__" data-id="pub.1129830274" data-style="small_rectangle"></span>
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4 changes: 2 additions & 2 deletions docs/source/installation.rst
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Expand Up @@ -19,12 +19,12 @@ Development Version

To work with the latest development version, install from GitHub_ using::

pip install git+https://github.com/theislab/scvelo@develop
pip install git+https://github.com/theislab/scvelo@main

or::

git clone https://github.com/theislab/scvelo && cd scvelo
git checkout --track origin/develop
git checkout --track origin/main
pip install -e .

``-e`` is short for ``--editable`` and links the package to the original cloned
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1 change: 0 additions & 1 deletion docs/source/perspectives/index.rst
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Expand Up @@ -21,7 +21,6 @@ transcriptional boost in erythroid lineage, and misleading arrow projections in

Notebook: `Perspectives <Perspectives>`_

|
Kinetic parameter analysis
^^^^^^^^^^^^^^^^^^^^^^^^^^
.. image:: https://user-images.githubusercontent.com/31883718/130656606-00bd44be-9071-4008-be1b-244fa9c2d244.png
Expand Down
21 changes: 21 additions & 0 deletions docs/source/references.bib
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Expand Up @@ -62,3 +62,24 @@ @article{Wolf19
title = {{PAGA}: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells},
journal = {Genome Biology}
}

@article{Gayoso2023,
title = {Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells},
url = {http://dx.doi.org/10.1038/s41592-023-01994-w},
doi = {10.1038/s41592-023-01994-w},
journal = {Nature Methods},
publisher = {Springer Science and Business Media LLC},
author = {Adam Gayoso and Philipp Weiler and Mohammad Lotfollahi and Dominik Klein and Justin Hong and Aaron Streets and Fabian J. Theis and Nir Yosef},
year = {2023},
month = sep
}

@article{Weiler2023,
title = {Unified fate mapping in multiview single-cell data},
url = {http://dx.doi.org/10.1101/2023.07.19.549685},
DOI = {10.1101/2023.07.19.549685},
publisher = {Cold Spring Harbor Laboratory},
author = {Philipp Weiler and Marius Lange and Michal Klein and Dana Pe{\textquotesingle}er and Fabian J. Theis},
year = {2023},
month = jul
}
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