diff --git a/README.rst b/README.rst index 80abe01f9..149e85a59 100644 --- a/README.rst +++ b/README.rst @@ -13,12 +13,13 @@ CellRank 2: Unified fate mapping in multiview single-cell data **CellRank** is a modular framework to study cellular dynamics based on Markov state modeling of multi-view single-cell data. See our `documentation`_, and the `CellRank 1`_ and `CellRank 2 manuscript`_ to learn more. -See `here `_ for how to properly cite our work. + +.. important:: + Please refer to :doc:`our citation guide ` to cite our software correctly. CellRank scales to large cell numbers, is fully compatible with the `scverse`_ ecosystem, and easy to use. In the backend, it is powered by `pyGPCCA`_ (`Reuter et al. (2018)`_). Feel -free to open an `issue`_ or send us an `email`_ if you encounter a bug, need our help or just -want to make a comment/suggestion. +free to open an `issue`_ if you encounter a bug, need our help or just want to make a comment/suggestion. CellRank's key applications --------------------------- @@ -63,8 +64,7 @@ CellRank's key applications .. _pyGPCCA: https://github.com/msmdev/pyGPCCA .. _CellRank 1: https://www.nature.com/articles/s41592-021-01346-6 -.. _CellRank 2 manuscript: https://doi.org/10.1101/2023.07.19.549685 +.. _CellRank 2 manuscript: https://doi.org/10.1038/s41592-024-02303-9 .. _documentation: https://cellrank.org -.. _email: mailto:info@cellrank.org .. _issue: https://github.com/theislab/cellrank/issues/new/choose diff --git a/docs/_static/img/dark_mode_overview.png b/docs/_static/img/dark_mode_overview.png index 2c3a67055..01b8112e4 100644 Binary files a/docs/_static/img/dark_mode_overview.png and b/docs/_static/img/dark_mode_overview.png differ diff --git a/docs/_static/img/light_mode_overview.png b/docs/_static/img/light_mode_overview.png index 8ac43c34c..0dc056db0 100644 Binary files a/docs/_static/img/light_mode_overview.png and b/docs/_static/img/light_mode_overview.png differ diff --git a/docs/index.rst b/docs/index.rst index 193ce17f6..2381524d1 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -14,17 +14,21 @@ CellRank 2: Unified fate mapping in multiview single-cell data **CellRank** :cite:`lange:22,weiler:24` is a modular framework to study cellular dynamics based on Markov state modeling of multi-view single-cell data. See :doc:`about CellRank ` to learn more and :doc:`our citation guide ` for guidance on -citing our work correctly. Also, read our `recent preprint `_ to see the new CellRank 2 features in action. +citing our work correctly. Two peer-reviewed publications accompany our software: +- `CellRank for directed single-cell fate mapping ` +- `CellRank 2: unified fate mapping in multiview single-cell data ` + +.. important:: + Please refer to :doc:`our citation guide ` to cite our software correctly. CellRank scales to large cell numbers, is fully compatible with the `scverse`_ ecosystem, and is easy to use. In the backend, it is powered by the `pyGPCCA package `_ :cite:`reuter:19,reuter:22`. Feel -free to open an `issue`_ or send us an `email `_ if you encounter a bug, need our help or -just want to make a comment/suggestion. +free to open an `issue`_ if you encounter a bug, need our help or just want to make a comment/suggestion. .. important:: If you're moving from CellRank 1 to CellRank 2, check out :doc:`../about/version2`. -CellRank's Key Applications +CellRank's key applications --------------------------- - Estimate differentiation direction based on a varied number of biological priors, including :doc:`pseudotime `, @@ -37,10 +41,10 @@ CellRank's Key Applications - Visualize and cluster :doc:`gene expression trends `. - ... and much more, check out our :doc:`API `. -Getting Started with CellRank +Getting started with CellRank ----------------------------- We have :doc:`notebooks/tutorials/index` to help you getting started. To see CellRank in action, explore our -manuscript :cite:`lange:22` in Nature Methods. +manuscripts :cite:`lange:22,weiler:24` in Nature Methods. Contributing ------------