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.. role:: small
{doc}rapids-singlecell <rapids_singlecell:index> by Severin Dicks provides a scanpy-like API with accelerated operations implemented on GPU.
100 people have contributed to Scanpy's source code!
Of course, contributions to the project are not limited to direct modification of the source code. Many others have improved the project by building on top of it, participating in development discussions, helping others with usage, or by showing off what it's helped them accomplish.
Thanks to all our contributors for making this project possible!
We've moved our forums and have a new publicly available chat!
- Our discourse forum has migrated to a joint scverse forum (discourse.scverse.org).
- Our private developer Slack has been replaced by a public Zulip chat (scverse.zulipchat.com).
Two large toolkits extending our ecosystem to new modalities have had their manuscripts published!
- Muon, a framework for multimodal has been published in Genome Biology.
- Squidpy a toolkit for working with spatial single cell data has been published in Nature Methods.
Scanpy's counterpart for RNA velocity, scVelo, made it on the cover of Nature Biotechnology [tweet].
Genome Biology: Celebrating 20 Years of Genome Biology selected the initial Scanpy paper for the year 2018 among 20 papers for 20 years [tweet].
In a joint initiative, the Wellcome Sanger Institute, the Human Cell Atlas, and the CZI distribute datasets related to COVID-19 via anndata's h5ad files: covid19cellatlas.org. It wasn't anticipated that the initial idea of sharing and backing an on-disk representation of AnnData would become so widely adopted. Curious? Read up more on the format.
Single-cell RNA-seq analysis software providers scramble to offer solutions mentions Scanpy along with Seurat as the two major open source software packages for single-cell analysis [pdf].
Scanpy has been selected an essential open source software for science by CZI among 32 projects, along with giants such as Scipy, Numpy, Pandas, Matplotlib, scikit-learn, scikit-image/plotly, pip, jupyterhub/binder, Bioconda, Seurat, Bioconductor, and others.
Nature Biotechnology reviews more than 70 TI tools and ranks PAGA as the best graph-based trajectory inference method, and overall, among the top 3.
The Science “Breakthrough of the Year 2018”, Development cell by cell, mentions the first application of PAGA {cite:p}Plass2018 among 5 papers.